diff --git a/README.md b/README.md index a1969e3de06b7bd81082aaa431dca106f4e65ac1..07970a39d29bfc3f976358f0bb9083f2d9354063 100644 --- a/README.md +++ b/README.md @@ -105,16 +105,29 @@ left out. A model that leaves the list keeps the results it already has. ## sentence-transformers -The 2026-11-03 sweep tests the top 10 Hub models tagged `sentence-transformers`, -sorted by trending score, plus the highest-ranked MultiVectorEncoder at rank 15. -The selection and checkpoint revisions are frozen in -`validation/sentence-transformers/2026-11-03/trending.json`. No failed candidate -was replaced with a passing model. +The 2026-11-03 sweep covers the top 100 models in each Hub listing tagged +`sentence-transformers`: [Trending](https://huggingface.co/models?library=sentence-transformers&sort=trending) +and [Downloads](https://huggingface.co/models?library=sentence-transformers&sort=downloads). +There are 164 distinct checkpoints, with 36 appearing in both lists. The exact +ordered lists, checkpoint revisions, and capture time are frozen in +`validation/sentence-transformers/2026-11-03-top100/`. Every eligible checkpoint +was tested afresh; failures were not replaced with passing models. SparseEncoder, +non-native quantized formats, and unrelated classification tasks have explicit +`EXCLUDED` records. `selection_rank` records the snapshot's Trending rank; +Downloads ranks are in the raw results and row notes. The Space's Trending and +Downloads views use the live Hub ordering, which can change after this snapshot. + +| Snapshot | PASS | Output check failed | Load/forward failed | Excluded | Total | +|---|---:|---:|---:|---:|---:| +| Trending | 71 | 10 | 9 | 10 | 100 | +| Downloads | 80 | 6 | 12 | 2 | 100 | +| Unique models | 119 | 15 | 18 | 12 | 164 | SentenceTransformer uses `encode_query`, `encode_document`, and `similarity`; CrossEncoder uses `predict` on query/document pairs; MultiVectorEncoder uses query/document encoding followed by native MaxSim. Saved retrieval prompts are -applied. All three paths produce four scores on `neuron:0`, with batch size 4: +applied, with model-card task/prompt overrides recorded in each script where +needed. All three paths aim to produce four scores on `neuron:0`, with batch size 4: ```python query = "Which planet is known as the Red Planet?" @@ -126,58 +139,55 @@ documents = [ ] ``` -`PASS` requires four finite scores, Mars ranked first, and CPU score agreement -using `atol=rtol=0.001` at the same precision. `FAIL(output)` means the output -check failed, even when inference completed. Every completed run is repeated; -all repeats produced identical scores. Scores are in original document order -and are not comparable between models. - -The sweep uses native eager PyTorch with SDPA, without an explicit -`torch.compile` wrapper, on one logical Neuron device of a Trainium2 instance. -FP32 is used except for `nvidia/Nemotron-3.5-Rerank-8B-BF16`: allocating its FP32 -weights exhausted device memory. Its BF16 retry ran and ranked Mars first, but -the maximum CPU score difference was 0.008537, so it is `FAIL(output)` under the -strict parity criterion. The other ten records pass, including the supplementary -MultiVectorEncoder. - -`google/embeddinggemma-2` uses its documented text-only configuration -(`vision_config=None`, `audio_config=None`); full multimodal loading with SDPA -failed on the audio encoder. It required an upgrade from Transformers 5.17.0. -The MiniLM run used 5.17.0; the other final runs used 5.22.1. Kanana uses its -required `trust_remote_code=True` at the recorded revision. Perplexity uses the -reference PyTorch gated-attention implementation without `flash-linear-attention`. -Sentence Transformers is pinned to commit -`6be0abf38d00d70bb3c732131df59ad073ff3768` (6.3.0.dev0). - -This validates one text retrieval example, not general retrieval quality, -throughput, training, image/audio inputs, tensor parallelism, or multi-device -execution. SparseEncoder was not tested. All 11 models were rerun with device -memory monitoring. The memory columns report the highest observed sum of Neuron -runtime HBM categories (tensors, code, constants, scratchpad, miscellaneous runtime -allocations, and DMA rings) on logical device 0, sampled in-process at a target -interval of 100 ms. Monitoring begins before model transfer and ends after the -final inference is synchronized. Capacity is queried from +`PASS` requires native Neuron execution, four finite scores, Mars ranked first, +CPU score agreement at the same precision (`atol=rtol=0.001`), and a stable repeat +with the same tolerance. `FAIL(output)` means execution completed but a ranking, +parity, or repeat check failed. A ranking failure can also occur on CPU; it does +not by itself indicate a Neuron defect. Loading and forward failures include +CPU-side incompatibilities, gated checkpoint access failures, and native-device +errors; the recorded stage and traceback distinguish them. Scores are in original +document order and are not comparable between models. Results describe this +configuration and example, not universal model support or retrieval quality. + +The sweep uses native eager PyTorch, without an explicit `torch.compile` wrapper, +on one logical Neuron device per model on Trainium2. Four independent workers +use separate physical devices; this is not tensor parallelism. SDPA is preferred, +with eager attention retried where a checkpoint does not support it. FP32 is the +default, with BF16 for large models or after allocation failure. Final precision, +attention, configuration overrides, and earlier attempts are retained. Some +checkpoints require `trust_remote_code=True`; checkpoint revisions are pinned, +but remote code referenced from another repository is not separately pinned. +Transformers is 5.22.1, and Sentence Transformers is pinned to commit +`6be0abf38d00d70bb3c732131df59ad073ff3768` (6.3.0.dev0). The compiler is +`neuronx-cc 2.28.4568.0+0163fa9e`; each row and script record the tested stack. + +This validates one text retrieval example, not throughput, training, image/audio +inputs, tensor parallelism, or multi-device execution. The memory columns report +the highest observed sum of Neuron runtime HBM categories (tensors, code, +constants, scratchpad, miscellaneous runtime allocations, and DMA rings), sampled +in-process at a target interval of 100 ms. Monitoring begins before model transfer +and ends after the final inference is synchronized. Capacity comes from `torch.neuron.get_device_properties(0).total_memory`: 24 GiB on this instance. Values use GiB (bytes / 2**30), matching existing dataset entries despite the -Space's `Memory (GB)` label. This is a sampled peak; short transients between -samples may be missed. Allocator high-water marks are recorded separately in -the raw results and are not substituted for total runtime HBM usage. The installed -`neuron-monitor` did not discover these native processes, so the runtime's HBM -counters were queried directly. Per-category samples are retained in -`validation/sentence-transformers/2026-11-03/memory_samples/`. - -Wall time includes model loading, CPU reference, first Neuron execution/compilation, -the repeat, and monitoring overhead; it is not inference latency. Start timestamps -come from the rerun launcher. `runner` names the encoder class; `neuron_cores=1` describes the single -logical device used, not a tensor-parallel degree. - -Full scores, versions, configuration, and earlier unsuccessful attempts are in -`validation/sentence-transformers/2026-11-03/validation_results.json`, with final -scores also available as CSV. The initial results before memory monitoring are -preserved in `initial_validation_results.json` and `initial_validation_results.csv`. -Each row includes the standalone script used for the monitored rerun. These scripts write `result.json` and exit nonzero -if retrieval or CPU parity fails. No compiled cache from this sweep has been -published. +Space's `Memory (GB)` label. Short transients between samples may be missed. +Allocator high-water marks are retained separately in raw results. The installed +`neuron-monitor` did not discover these native processes, so runtime HBM counters +were queried directly. Failed runs without a completed capture leave memory +empty rather than recording zero. Per-category samples are retained under the +sweep's `memory_samples/` directory. + +Wall time covers imports, loading, the CPU reference, first Neuron execution and +compilation, the repeat, and monitoring overhead. It is not per-query inference +latency, and concurrent workers can affect timing. `runner` names the encoder +class; `neuron_cores=1` means one logical device, not a tensor-parallel degree. + +Full scores, configuration, prior attempts, and per-view counts are in +`validation/sentence-transformers/2026-11-03-top100/results.json`, with a compact +`results.csv` alongside it. Each tested row includes its standalone `run_py`, +which writes `result.json` and exits nonzero when validation fails. Failure logs +are retained in `logs/`. No compiled cache was published. The earlier top-10 +study and supplementary MultiVectorEncoder remain available in +`validation/sentence-transformers/2026-11-03/` as historical evidence. ## Layout diff --git a/data/trn2/neuronxcc-2.28.4568.0+0163fa9e/sentence-transformers-6.3.0.dev0.parquet b/data/trn2/neuronxcc-2.28.4568.0+0163fa9e/sentence-transformers-6.3.0.dev0.parquet index 8158f0f00a2eb6a0e72201291da90b41a6a0d6b7..5f1c6c29446133ae0bcc2d64a272fc99b6a3d485 100644 Binary files a/data/trn2/neuronxcc-2.28.4568.0+0163fa9e/sentence-transformers-6.3.0.dev0.parquet and b/data/trn2/neuronxcc-2.28.4568.0+0163fa9e/sentence-transformers-6.3.0.dev0.parquet differ diff --git a/validation/sentence-transformers/2026-11-03-top100/downloads.json b/validation/sentence-transformers/2026-11-03-top100/downloads.json new file mode 100644 index 0000000000000000000000000000000000000000..23acbf9dbcc900b54490db5717bb0cea901db291 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/downloads.json @@ -0,0 +1 @@ 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b/validation/sentence-transformers/2026-11-03-top100/logs/007.log new file mode 100644 index 0000000000000000000000000000000000000000..030125b4ab04ae6028ee9fa1f4ba9c25d5036032 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/007.log @@ -0,0 +1,13 @@ +[transformers] Unrecognized keys in `rope_parameters` for 'rope_type'='yarn': {'apply_yarn_scaling'} +[transformers] Mistral3Model LOAD REPORT from: nvidia/Nemotron-3.5-Rerank-8B-BF16 +Key | Status | | +----------------------------+------------+--+- +language_model.score.weight | UNEXPECTED | | + +Notes: +- UNEXPECTED: can be ignored when loading from different task/architecture; not ok if you expect identical arch. +CPU [-2.699960470199585, -1.0288699865341187, -2.2972545623779297, -2.0584821701049805] +2026-Nov-03 15:28:51.541569 2133586:2133586 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +{"index": 7, "model": "nvidia/Nemotron-3.5-Rerank-8B-BF16", "revision": "f88f8d9104726747791283ab156d2fcdb29e90a7", "trending_rank": 7, "downloads_rank": null, "class": "CrossEncoder", "dtype": "bfloat16", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:28:39.934071+00:00", "physical_visible_core": "0", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 1.2689191922545433, "prompts": {}, "parameter_dtypes": ["torch.bfloat16"], "cpu_scores": [-2.699960470199585, -1.0288699865341187, -2.2972545623779297, -2.0584821701049805], "cpu_seconds": 1.485507046803832, "cpu_top_document": 2, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 0.4639179026708007, "neuron_scores": [-2.700716495513916, -1.0203332901000977, -2.303680419921875, -2.0575268268585205], "max_abs_error": 0.008536696434020996, "neuron_top_document": 2, "mars_first": true, "cpu_parity": false, "neuron_repeat_seconds": 0.16087585594505072, "repeat_max_abs_error": 0.0, "repeat_stable": true, "status": "executed", "result": "FAIL(output)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 23, "sample_interval_seconds": 0.1, "peak_bytes": 16937250251, "peak_categories": {"code": 8118208, "tensors": 16848523264, "constants": 1605643, "scratchpad": 67108864, "misc": 10510848, "dma_rings": 1383424}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 16791547648, "allocator_peak_reserved_bytes": 16848519168, "total_seconds": 20.877234225161374} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/021.log b/validation/sentence-transformers/2026-11-03-top100/logs/021.log new file mode 100644 index 0000000000000000000000000000000000000000..36e4619e414f0afc2f96078ecc006b345e6f4ac6 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/021.log @@ -0,0 +1,5 @@ +CPU [0.4586111605167389, 0.6143702864646912, 0.5348622798919678, 0.615755021572113] +2026-Nov-03 15:31:46.722403 2188264:2188264 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +{"index": 21, "model": "Omartificial-Intelligence-Space/Arabic-Triplet-Matryoshka-V2", "revision": "17b87422aa4bfb3b478369299e701070b308314f", "trending_rank": 21, "downloads_rank": null, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:31:28.531464+00:00", "physical_visible_core": "8", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 6.291727272793651, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "embedding_devices": ["neuron:0", "neuron:0"], "cpu_scores": [0.4586111605167389, 0.6143702864646912, 0.5348622798919678, 0.615755021572113], "cpu_seconds": 0.3750715795904398, "cpu_top_document": 4, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 105.76572554465383, "neuron_scores": [0.4586114287376404, 0.6143702268600464, 0.534862220287323, 0.6157552003860474], "max_abs_error": 2.682209014892578e-07, "neuron_top_document": 4, "mars_first": false, "cpu_parity": true, "neuron_repeat_seconds": 0.09435997158288956, "repeat_max_abs_error": 0.0, "repeat_stable": true, "status": "executed", "result": "FAIL(output)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 1059, "sample_interval_seconds": 0.1, "peak_bytes": 695672385, "peak_categories": {"code": 6654512, "tensors": 606081024, "constants": 3473425, "scratchpad": 67108864, "misc": 9832960, "dma_rings": 2521600}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 588299648, "allocator_peak_reserved_bytes": 606076928, "total_seconds": 131.14824269991368} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/023.log b/validation/sentence-transformers/2026-11-03-top100/logs/023.log new file mode 100644 index 0000000000000000000000000000000000000000..83b696da3fc476f73844080c577fb8bfd892f90e --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/023.log @@ -0,0 +1,62 @@ +httpx.HTTPStatusError: Client error '403 Forbidden' for url 'https://huggingface.co/litert-community/embeddinggemma-300m/resolve/459f1d37fec9635eb1730ebdbc219bfc3226c8e7/modules.json' +For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/403 + +The above exception was the direct cause of the following exception: + +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/023/run.py", line 50, in + model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']}) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 193, in __init__ + super().__init__( + ~~~~~~~~~~~~~~~~^ + model_name_or_path=model_name_or_path, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ...<13 lines>... + default_prompt_name=default_prompt_name, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 256, in __init__ + modules, self.module_kwargs = self._load_modules( + ~~~~~~~~~~~~~~~~~~^ + model_name_or_path, + ^^^^^^^^^^^^^^^^^^^ + ...<7 lines>... + config_kwargs=config_kwargs, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 1190, in _load_modules + modules_json_path = load_file_path( + model_name_or_path, + ...<4 lines>... + local_files_only=local_files_only, + ) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/file_io.py", line 208, in load_file_path + return hf_hub_download( + model_name_or_path, + ...<6 lines>... + local_files_only=local_files_only, + ) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/utils/_validators.py", line 89, in _inner_fn + return fn(*args, **kwargs) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/utils/_http.py", line 266, in _inner + return fn(*args, **kwargs) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py", line 1047, in hf_hub_download + return _hf_hub_download_to_cache_dir( + # Destination + ...<15 lines>... + dry_run=dry_run, + ) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py", line 1194, in _hf_hub_download_to_cache_dir + _raise_on_head_call_error(head_call_error, force_download, local_files_only) + ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py", line 1953, in _raise_on_head_call_error + raise head_call_error +huggingface_hub.errors.GatedRepoError: 403 Client Error. (Request ID: Root=1-6ae9fe77-5b99b3f12170976f33af1862;24fb7211-ac04-4557-9d7c-d58c3b8e6212) + +Cannot access gated repo for url https://huggingface.co/litert-community/embeddinggemma-300m/resolve/459f1d37fec9635eb1730ebdbc219bfc3226c8e7/modules.json. +Access to model litert-community/embeddinggemma-300m is restricted and you are not in the authorized list. Visit https://huggingface.co/litert-community/embeddinggemma-300m to ask for access. +{"index": 23, "model": "litert-community/embeddinggemma-300m", "revision": "459f1d37fec9635eb1730ebdbc219bfc3226c8e7", "trending_rank": 23, "downloads_rank": null, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:31:58.747378+00:00", "physical_visible_core": "12", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "status": "error", "stage": "load_cpu", "error_type": "GatedRepoError", "error": "403 Client Error. (Request ID: Root=1-6ae9fe77-5b99b3f12170976f33af1862;24fb7211-ac04-4557-9d7c-d58c3b8e6212)\n\nCannot access gated repo for url https://huggingface.co/litert-community/embeddinggemma-300m/resolve/459f1d37fec9635eb1730ebdbc219bfc3226c8e7/modules.json.\nAccess to model litert-community/embeddinggemma-300m is restricted and you are not in the authorized list. Visit https://huggingface.co/litert-community/embeddinggemma-300m to ask for access.", "traceback": "httpx.HTTPStatusError: Client error '403 Forbidden' for url 'https://huggingface.co/litert-community/embeddinggemma-300m/resolve/459f1d37fec9635eb1730ebdbc219bfc3226c8e7/modules.json'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/403\n\nThe above exception was the direct cause of the following exception:\n\nTraceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/023/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1190, in _load_modules\n modules_json_path = load_file_path(\n model_name_or_path,\n ...<4 lines>...\n local_files_only=local_files_only,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/file_io.py\", line 208, in load_file_path\n return hf_hub_download(\n model_name_or_path,\n ...<6 lines>...\n local_files_only=local_files_only,\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/utils/_validators.py\", line 89, in _inner_fn\n return fn(*args, **kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/utils/_http.py\", line 266, in _inner\n return fn(*args, **kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py\", line 1047, in hf_hub_download\n return _hf_hub_download_to_cache_dir(\n # Destination\n ...<15 lines>...\n dry_run=dry_run,\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py\", line 1194, in _hf_hub_download_to_cache_dir\n _raise_on_head_call_error(head_call_error, force_download, local_files_only)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py\", line 1953, in _raise_on_head_call_error\n raise head_call_error\nhuggingface_hub.errors.GatedRepoError: 403 Client Error. (Request ID: Root=1-6ae9fe77-5b99b3f12170976f33af1862;24fb7211-ac04-4557-9d7c-d58c3b8e6212)\n\nCannot access gated repo for url https://huggingface.co/litert-community/embeddinggemma-300m/resolve/459f1d37fec9635eb1730ebdbc219bfc3226c8e7/modules.json.\nAccess to model litert-community/embeddinggemma-300m is restricted and you are not in the authorized list. Visit https://huggingface.co/litert-community/embeddinggemma-300m to ask for access.\n", "result": "FAIL(load)", "total_seconds": 8.972315741702914} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/024.log b/validation/sentence-transformers/2026-11-03-top100/logs/024.log new file mode 100644 index 0000000000000000000000000000000000000000..1a3528235119fb28c98c8b1240674d233cb72486 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/024.log @@ -0,0 +1,6 @@ +Default prompt name is set to 'default'. This prompt applies unless overridden by `prompt`, `prompt_name`, or a method-specific prompt, including an empty prompt. +CPU [0.5104122161865234, 0.8333847522735596, 0.5737250447273254, 0.6311128735542297] +2026-Nov-03 15:33:26.885580 2200020:2200020 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +{"index": 24, "model": "Qwen/Qwen3-VL-Embedding-8B", "revision": "2c4565515e0f265c6511776e7193b22c0968ddc7", "trending_rank": 24, "downloads_rank": 54, "class": "SentenceTransformer", "dtype": "bfloat16", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:32:09.263638+00:00", "physical_visible_core": "12", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 45.57155937794596, "prompts": {"query": "", "document": "", "default": "Represent the user's input."}, "parameter_dtypes": ["torch.bfloat16"], "embedding_devices": ["neuron:0", "neuron:0"], "cpu_scores": [0.5104122161865234, 0.8333847522735596, 0.5737250447273254, 0.6311128735542297], "cpu_seconds": 11.08764569554478, "cpu_top_document": 2, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 30.12761875614524, "neuron_scores": [0.5109585523605347, 0.8327626585960388, 0.5716332197189331, 0.6295062899589539], "max_abs_error": 0.002091825008392334, "neuron_top_document": 2, "mars_first": true, "cpu_parity": false, "neuron_repeat_seconds": 0.4174205930903554, "repeat_max_abs_error": 0.0, "repeat_stable": true, "status": "executed", "result": "FAIL(output)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 330, "sample_interval_seconds": 0.1, "peak_bytes": 16529538997, "peak_categories": {"code": 14566248, "tensors": 16414412800, "constants": 4571149, "scratchpad": 67108864, "misc": 24082496, "dma_rings": 4797440}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 16390182848, "allocator_peak_reserved_bytes": 16414408704, "total_seconds": 119.78512970823795} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/029.log b/validation/sentence-transformers/2026-11-03-top100/logs/029.log new file mode 100644 index 0000000000000000000000000000000000000000..74c62274c98747dad18003d6f134789fcd99888c --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/029.log @@ -0,0 +1,48 @@ +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/029/run.py", line 50, in + model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']}) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 193, in __init__ + super().__init__( + ~~~~~~~~~~~~~~~~^ + model_name_or_path=model_name_or_path, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ...<13 lines>... + default_prompt_name=default_prompt_name, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 256, in __init__ + modules, self.module_kwargs = self._load_modules( + ~~~~~~~~~~~~~~~~~~^ + model_name_or_path, + ^^^^^^^^^^^^^^^^^^^ + ...<7 lines>... + config_kwargs=config_kwargs, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 1200, in _load_modules + return self._load_default_modules(model_name_or_path, **load_kwargs) + ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 1272, in _load_default_modules + transformer_model = Transformer( + model_name_or_path, + ...<4 lines>... + backend=self.backend, + ) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 92, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 839, in __init__ + config, is_peft_model = self._load_config(model_name_or_path, backend, config_kwargs) + ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 2259, in _load_config + return AutoConfig.from_pretrained(model_name_or_path, **config_kwargs), False + ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/configuration_auto.py", line 450, in from_pretrained + raise ValueError( + ...<2 lines>... + ) +ValueError: Unrecognized model in BrunoHays/embeddinggemma-2-nullspace-audio. Should have a `model_type` key in its config.json. +{"index": 29, "model": "BrunoHays/embeddinggemma-2-nullspace-audio", "revision": "4e54c6816e4ba368be62885788974458f2748adf", "trending_rank": 29, "downloads_rank": null, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:34:11.569070+00:00", "physical_visible_core": "12", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "status": "error", "stage": "load_cpu", "error_type": "ValueError", "error": "Unrecognized model in BrunoHays/embeddinggemma-2-nullspace-audio. Should have a `model_type` key in its config.json.", "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/029/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1200, in _load_modules\n return self._load_default_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 1272, in _load_default_modules\n transformer_model = Transformer(\n model_name_or_path,\n ...<4 lines>...\n backend=self.backend,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 839, in __init__\n config, is_peft_model = self._load_config(model_name_or_path, backend, config_kwargs)\n ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2259, in _load_config\n return AutoConfig.from_pretrained(model_name_or_path, **config_kwargs), False\n ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/configuration_auto.py\", line 450, in from_pretrained\n raise ValueError(\n ...<2 lines>...\n )\nValueError: Unrecognized model in BrunoHays/embeddinggemma-2-nullspace-audio. Should have a `model_type` key in its config.json.\n", "result": "FAIL(load)", "total_seconds": 24.265914521180093} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/031.log b/validation/sentence-transformers/2026-11-03-top100/logs/031.log new file mode 100644 index 0000000000000000000000000000000000000000..8e9dc82b0f9f6486beb3b197bde960f6055cc9ee --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/031.log @@ -0,0 +1,6 @@ +[transformers] We found `hidden_act="gelu"` in this Gemma config. This is a legacy value of the official releases but it is meant to target the tanh approximation. Setting `hidden_act="gelu_pytorch_tanh"` instead. +CPU [0.9997572302818298, 0.9997515082359314, 0.9998114705085754, 0.9997087121009827] +2026-Nov-03 15:35:46.446477 2247012:2247012 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +{"index": 31, "model": "BAAI/bge-reranker-v2-gemma", "revision": "1787044f8b6fb740a9de4557c3a12377f84d9e17", "trending_rank": 31, "downloads_rank": null, "class": "CrossEncoder", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:34:37.563999+00:00", "physical_visible_core": "12", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 6.2028824258595705, "prompts": {}, "parameter_dtypes": ["torch.float32"], "cpu_scores": [0.9997572302818298, 0.9997515082359314, 0.9998114705085754, 0.9997087121009827], "cpu_seconds": 32.531744067557156, "cpu_top_document": 3, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 45.031333486549556, "neuron_scores": [0.9997572898864746, 0.9997514486312866, 0.9998114109039307, 0.9997087717056274], "max_abs_error": 5.960464477539063e-08, "neuron_top_document": 3, "mars_first": false, "cpu_parity": true, "neuron_repeat_seconds": 0.09113490767776966, "repeat_max_abs_error": 0.0, "repeat_stable": true, "status": "executed", "result": "FAIL(output)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 460, "sample_interval_seconds": 0.1, "peak_bytes": 10210461645, "peak_categories": {"code": 20083904, "tensors": 10112471040, "constants": 1474573, "scratchpad": 67108864, "misc": 8413952, "dma_rings": 909312}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 10061462720, "allocator_peak_reserved_bytes": 10112466944, "total_seconds": 123.40695661306381} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/033.log b/validation/sentence-transformers/2026-11-03-top100/logs/033.log new file mode 100644 index 0000000000000000000000000000000000000000..e09b9acebfc91ca08ec8a20d9a210536c7ad9a6b --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/033.log @@ -0,0 +1,65 @@ +/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/configuration_utils.py:723: FutureWarning: `rope_scaling` is deprecated and will be removed in a future version. Set `rope_parameters` instead, with `rope_type` and `rope_theta` included. + warnings.warn( +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/033/run.py", line 64, in + stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1) + ~~~~~^^ + File "/tmp/neuron-top100-sweep/runs/033/run.py", line 59, in score + q=(model.encode([query],batch_size=4,show_progress_bar=False,**kw,**SPEC['query_kwargs']) if SPEC.get('query_kwargs') else model.encode_query([query],batch_size=4,show_progress_bar=False,**kw)) + ~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 370, in encode_query + return self.encode( + ~~~~~~~~~~~^ + inputs=inputs, + ^^^^^^^^^^^^^^ + ...<14 lines>... + **kwargs, + ^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py", line 124, in decorate_context + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 895, in encode + all_embeddings = self._inference(inputs, device=device, **inference_kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py", line 124, in decorate_context + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 963, in _inference + out_features = self(features, **kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 600, in forward + input = module(input, **module_kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 1647, in forward + model_output = model_method(**filtered_kwargs) + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Snowflake/snowflake_hyphen_arctic_hyphen_embed_hyphen_m_hyphen_v2_dot_0/95c2741480856aa9666782eb4afe11959938017f/modeling_hf_alibaba_nlp_gte.py", line 900, in forward + (embedding_output, attention_mask, rope_embeds, length) = self.embeddings( + ~~~~~~~~~~~~~~~^ + unpad_inputs, + ^^^^^^^^^^^^^ + ...<5 lines>... + inputs_embeds=inputs_embeds + ^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Snowflake/snowflake_hyphen_arctic_hyphen_embed_hyphen_m_hyphen_v2_dot_0/95c2741480856aa9666782eb4afe11959938017f/modeling_hf_alibaba_nlp_gte.py", line 391, in forward + rope_cos = rope_cos[position_ids].unsqueeze(2) # [bs, seq_len, 1, dim] + ~~~~~~~~^^^^^^^^^^^^^^ +IndexError: index 140493294592752 is out of bounds for dimension 0 with size 14 +{"index": 33, "model": "Snowflake/snowflake-arctic-embed-m-v2.0", "revision": "95c2741480856aa9666782eb4afe11959938017f", "trending_rank": 33, "downloads_rank": null, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": true, "config_kwargs": {"use_memory_efficient_attention": false, "unpad_inputs": false}, "excluded": null, "exclusion": null, "reason": "Checkpoint custom code supports standard SDPA when xformers attention and input unpadding are disabled.", "started_at": "2026-11-03T16:00:36.977122+00:00", "physical_visible_core": "0", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 3.8345429748296738, "prompts": {"query": "query: ", "document": ""}, "parameter_dtypes": ["torch.float32"], "status": "error", "stage": "cpu_inference", "error_type": "IndexError", "error": "index 140493294592752 is out of bounds for dimension 0 with size 14", "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/033/run.py\", line 64, in \n stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/033/run.py\", line 59, in score\n q=(model.encode([query],batch_size=4,show_progress_bar=False,**kw,**SPEC['query_kwargs']) if SPEC.get('query_kwargs') else model.encode_query([query],batch_size=4,show_progress_bar=False,**kw))\n ~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 370, in encode_query\n return self.encode(\n ~~~~~~~~~~~^\n inputs=inputs,\n ^^^^^^^^^^^^^^\n ...<14 lines>...\n **kwargs,\n ^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 895, in encode\n all_embeddings = self._inference(inputs, device=device, **inference_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 963, in _inference\n out_features = self(features, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 600, in forward\n input = module(input, **module_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 1647, in forward\n model_output = model_method(**filtered_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Snowflake/snowflake_hyphen_arctic_hyphen_embed_hyphen_m_hyphen_v2_dot_0/95c2741480856aa9666782eb4afe11959938017f/modeling_hf_alibaba_nlp_gte.py\", line 900, in forward\n (embedding_output, attention_mask, rope_embeds, length) = self.embeddings(\n ~~~~~~~~~~~~~~~^\n unpad_inputs,\n ^^^^^^^^^^^^^\n ...<5 lines>...\n inputs_embeds=inputs_embeds\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Snowflake/snowflake_hyphen_arctic_hyphen_embed_hyphen_m_hyphen_v2_dot_0/95c2741480856aa9666782eb4afe11959938017f/modeling_hf_alibaba_nlp_gte.py\", line 391, in forward\n rope_cos = rope_cos[position_ids].unsqueeze(2) # [bs, seq_len, 1, dim]\n ~~~~~~~~^^^^^^^^^^^^^^\nIndexError: index 140493294592752 is out of bounds for dimension 0 with size 14\n", "result": "FAIL(forward)", "total_seconds": 12.881709131412208} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/034.log b/validation/sentence-transformers/2026-11-03-top100/logs/034.log new file mode 100644 index 0000000000000000000000000000000000000000..e73d12c57102f2a7996c649e7acb304e1425d2c8 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/034.log @@ -0,0 +1,6 @@ +Default prompt name is set to 'query'. This prompt applies unless overridden by `prompt`, `prompt_name`, or a method-specific prompt, including an empty prompt. +CPU [-8.125, 4.0625, -5.34375, -4.5625] +2026-Nov-03 15:37:25.459653 2272047:2272047 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +{"index": 34, "model": "Qwen/Qwen3-Reranker-8B", "revision": "77d193c791ed757ca307ee72715aa132723da912", "trending_rank": 34, "downloads_rank": null, "class": "CrossEncoder", "dtype": "bfloat16", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:36:33.649395+00:00", "physical_visible_core": "8", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 8.139716992154717, "prompts": {"query": "Given a web search query, retrieve relevant passages that answer the query"}, "parameter_dtypes": ["torch.bfloat16"], "cpu_scores": [-8.125, 4.0625, -5.34375, -4.5625], "cpu_seconds": 24.723026665858924, "cpu_top_document": 2, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 59.1664319653064, "neuron_scores": [-8.0625, 4.0625, -5.375, -4.5625], "max_abs_error": 0.0625, "neuron_top_document": 2, "mars_first": true, "cpu_parity": false, "neuron_repeat_seconds": 0.24539023637771606, "repeat_max_abs_error": 0.0, "repeat_stable": true, "status": "executed", "result": "FAIL(output)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 621, "sample_interval_seconds": 0.1, "peak_bytes": 19178892667, "peak_categories": {"code": 25923376, "tensors": 16521367552, "constants": 1425419, "scratchpad": 2617245696, "misc": 11091520, "dma_rings": 1839104}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 16468168832, "allocator_peak_reserved_bytes": 16521363456, "total_seconds": 126.22209540009499} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/054.log b/validation/sentence-transformers/2026-11-03-top100/logs/054.log new file mode 100644 index 0000000000000000000000000000000000000000..67e36c72d24bc3d34680a0fd90486a44c95629f8 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/054.log @@ -0,0 +1,69 @@ +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/054/run.py", line 50, in + model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']}) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 193, in __init__ + super().__init__( + ~~~~~~~~~~~~~~~~^ + model_name_or_path=model_name_or_path, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ...<13 lines>... + default_prompt_name=default_prompt_name, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 256, in __init__ + modules, self.module_kwargs = self._load_modules( + ~~~~~~~~~~~~~~~~~~^ + model_name_or_path, + ^^^^^^^^^^^^^^^^^^^ + ...<7 lines>... + config_kwargs=config_kwargs, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 1211, in _load_modules + return self._load_config_modules(model_name_or_path, **load_kwargs) + ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 1431, in _load_config_modules + module = module_class.load( + model_name_or_path, + ...<12 lines>... + **extra_load_kwargs, + ) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 2641, in load + return cls(model_name_or_path=model_name_or_path, **init_kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 92, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 870, in __init__ + self.processor = AutoProcessor.from_pretrained( + ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ + tokenizer_name_or_path if tokenizer_name_or_path is not None else model_name_or_path, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + **processor_kwargs, + ^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/processing_auto.py", line 350, in from_pretrained + return processor_class.from_pretrained( + ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ + pretrained_model_name_or_path, trust_remote_code=trust_remote_code, **kwargs + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/processing_utils.py", line 1749, in from_pretrained + args = cls._get_arguments_from_pretrained(pretrained_model_name_or_path, processor_dict, **kwargs) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/processing_utils.py", line 1889, in _get_arguments_from_pretrained + sub_processor = auto_processor_class.from_pretrained( + pretrained_model_name_or_path, subfolder=subfolder, **kwargs + ) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/feature_extraction_auto.py", line 329, in from_pretrained + config_dict, _ = FeatureExtractionMixin.get_feature_extractor_dict(pretrained_model_name_or_path, **kwargs) + ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/feature_extraction_utils.py", line 545, in get_feature_extractor_dict + raise OSError( + ...<4 lines>... + ) +OSError: Can't load feature extractor for 'HukukcuApp/tr-legal-embedding-gemma-2'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'HukukcuApp/tr-legal-embedding-gemma-2' is the correct path to a directory containing a preprocessor_config.json file +{"index": 54, "model": "HukukcuApp/tr-legal-embedding-gemma-2", "revision": "a33e497f3f123019d3b03fe40082992fffeac728", "trending_rank": 54, "downloads_rank": null, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:42:02.918547+00:00", "physical_visible_core": "0", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "status": "error", "stage": "load_cpu", "error_type": "OSError", "error": "Can't load feature extractor for 'HukukcuApp/tr-legal-embedding-gemma-2'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'HukukcuApp/tr-legal-embedding-gemma-2' is the correct path to a directory containing a preprocessor_config.json file", "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/054/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 870, in __init__\n self.processor = AutoProcessor.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n tokenizer_name_or_path if tokenizer_name_or_path is not None else model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n **processor_kwargs,\n ^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/processing_auto.py\", line 350, in from_pretrained\n return processor_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, trust_remote_code=trust_remote_code, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/processing_utils.py\", line 1749, in from_pretrained\n args = cls._get_arguments_from_pretrained(pretrained_model_name_or_path, processor_dict, **kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/processing_utils.py\", line 1889, in _get_arguments_from_pretrained\n sub_processor = auto_processor_class.from_pretrained(\n pretrained_model_name_or_path, subfolder=subfolder, **kwargs\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/feature_extraction_auto.py\", line 329, in from_pretrained\n config_dict, _ = FeatureExtractionMixin.get_feature_extractor_dict(pretrained_model_name_or_path, **kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/feature_extraction_utils.py\", line 545, in get_feature_extractor_dict\n raise OSError(\n ...<4 lines>...\n )\nOSError: Can't load feature extractor for 'HukukcuApp/tr-legal-embedding-gemma-2'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'HukukcuApp/tr-legal-embedding-gemma-2' is the correct path to a directory containing a preprocessor_config.json file\n", "result": "FAIL(load)", "total_seconds": 14.706041608005762} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/067.log b/validation/sentence-transformers/2026-11-03-top100/logs/067.log new file mode 100644 index 0000000000000000000000000000000000000000..c7726d132cf190f3eb519980a6a5026279616883 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/067.log @@ -0,0 +1,5 @@ +CPU [0.6934455037117004, 0.8071481585502625, 0.8093117475509644, 0.8064126968383789] +2026-Nov-03 15:45:21.230829 2446525:2446525 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +{"index": 67, "model": "moka-ai/m3e-base", "revision": "764b537a0e50e5c7d64db883f2d2e051cbe3c64c", "trending_rank": 67, "downloads_rank": null, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:45:11.803493+00:00", "physical_visible_core": "8", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 1.331957183778286, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "embedding_devices": ["neuron:0", "neuron:0"], "cpu_scores": [0.6934455037117004, 0.8071481585502625, 0.8093117475509644, 0.8064126968383789], "cpu_seconds": 0.14178986009210348, "cpu_top_document": 3, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 39.688529022969306, "neuron_scores": [0.6934453845024109, 0.807148277759552, 0.8093113899230957, 0.8064124584197998], "max_abs_error": 3.5762786865234375e-07, "neuron_top_document": 3, "mars_first": false, "cpu_parity": true, "neuron_repeat_seconds": 0.1130013084039092, "repeat_max_abs_error": 0.0, "repeat_stable": true, "status": "executed", "result": "FAIL(output)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 400, "sample_interval_seconds": 0.1, "peak_bytes": 560925521, "peak_categories": {"code": 6555520, "tensors": 471863296, "constants": 3178513, "scratchpad": 67108864, "misc": 9490112, "dma_rings": 2729216}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 452711936, "allocator_peak_reserved_bytes": 471859200, "total_seconds": 56.262652300298214} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/070.log b/validation/sentence-transformers/2026-11-03-top100/logs/070.log new file mode 100644 index 0000000000000000000000000000000000000000..dfed8394bf2f76aa0982b864fe3aa3faa3c89197 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/070.log @@ -0,0 +1,62 @@ +[transformers] A new version of the following files was downloaded from https://huggingface.co/jinaai/jina-bert-implementation: +- configuration_bert.py +. Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision. +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/070/run.py", line 50, in + model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']}) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 193, in __init__ + super().__init__( + ~~~~~~~~~~~~~~~~^ + model_name_or_path=model_name_or_path, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ...<13 lines>... + default_prompt_name=default_prompt_name, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 256, in __init__ + modules, self.module_kwargs = self._load_modules( + ~~~~~~~~~~~~~~~~~~^ + model_name_or_path, + ^^^^^^^^^^^^^^^^^^^ + ...<7 lines>... + config_kwargs=config_kwargs, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 1211, in _load_modules + return self._load_config_modules(model_name_or_path, **load_kwargs) + ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 1431, in _load_config_modules + module = module_class.load( + model_name_or_path, + ...<12 lines>... + **extra_load_kwargs, + ) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 2641, in load + return cls(model_name_or_path=model_name_or_path, **init_kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 92, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 839, in __init__ + config, is_peft_model = self._load_config(model_name_or_path, backend, config_kwargs) + ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 2259, in _load_config + return AutoConfig.from_pretrained(model_name_or_path, **config_kwargs), False + ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/configuration_auto.py", line 422, in from_pretrained + config_class = get_class_from_dynamic_module( + class_ref, pretrained_model_name_or_path, code_revision=code_revision, **kwargs + ) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py", line 625, in get_class_from_dynamic_module + return get_class_in_module(class_name, final_module, force_reload=force_download) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py", line 309, in get_class_in_module + module_spec.loader.exec_module(module) + ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^ + File "", line 759, in exec_module + File "", line 491, in _call_with_frames_removed + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_bert_hyphen_implementation/f3ec4cf7de7e561007f27c9efc7148b0bd713f81/configuration_bert.py", line 22, in + from transformers.onnx import OnnxConfig +ModuleNotFoundError: No module named 'transformers.onnx' +{"index": 70, "model": "jinaai/jina-embeddings-v2-base-en", "revision": "322d4d7e2f35e84137961a65af894fda0385eb7a", "trending_rank": 70, "downloads_rank": 88, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": true, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:45:55.385742+00:00", "physical_visible_core": "12", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "status": "error", "stage": "load_cpu", "error_type": "ModuleNotFoundError", "error": "No module named 'transformers.onnx'", "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/070/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 839, in __init__\n config, is_peft_model = self._load_config(model_name_or_path, backend, config_kwargs)\n ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2259, in _load_config\n return AutoConfig.from_pretrained(model_name_or_path, **config_kwargs), False\n ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/configuration_auto.py\", line 422, in from_pretrained\n config_class = get_class_from_dynamic_module(\n class_ref, pretrained_model_name_or_path, code_revision=code_revision, **kwargs\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 625, in get_class_from_dynamic_module\n return get_class_in_module(class_name, final_module, force_reload=force_download)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 309, in get_class_in_module\n module_spec.loader.exec_module(module)\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^\n File \"\", line 759, in exec_module\n File \"\", line 491, in _call_with_frames_removed\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_bert_hyphen_implementation/f3ec4cf7de7e561007f27c9efc7148b0bd713f81/configuration_bert.py\", line 22, in \n from transformers.onnx import OnnxConfig\nModuleNotFoundError: No module named 'transformers.onnx'\n", "result": "FAIL(load)", "total_seconds": 8.849647373892367} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/073.log b/validation/sentence-transformers/2026-11-03-top100/logs/073.log new file mode 100644 index 0000000000000000000000000000000000000000..f0e3cf1e5e1c7b67eac2df31cab0c82c24d017eb --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/073.log @@ -0,0 +1,70 @@ +[transformers] A new version of the following files was downloaded from https://huggingface.co/Alibaba-NLP/new-impl: +- configuration.py +. Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision. +/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/configuration_utils.py:723: FutureWarning: `rope_scaling` is deprecated and will be removed in a future version. Set `rope_parameters` instead, with `rope_type` and `rope_theta` included. + warnings.warn( +[transformers] A new version of the following files was downloaded from https://huggingface.co/Alibaba-NLP/new-impl: +- modeling.py +. Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision. +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/073/run.py", line 63, in + stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1) + ~~~~~^^ + File "/tmp/neuron-top100-sweep/runs/073/run.py", line 58, in score + q=model.encode_query([query],batch_size=4,show_progress_bar=False,**kw) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 370, in encode_query + return self.encode( + ~~~~~~~~~~~^ + inputs=inputs, + ^^^^^^^^^^^^^^ + ...<14 lines>... + **kwargs, + ^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py", line 124, in decorate_context + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 895, in encode + all_embeddings = self._inference(inputs, device=device, **inference_kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py", line 124, in decorate_context + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 963, in _inference + out_features = self(features, **kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 600, in forward + input = module(input, **module_kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 1647, in forward + model_output = model_method(**filtered_kwargs) + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py", line 901, in forward + (embedding_output, attention_mask, rope_embeds, length) = self.embeddings( + ~~~~~~~~~~~~~~~^ + unpad_inputs, + ^^^^^^^^^^^^^ + ...<5 lines>... + inputs_embeds=inputs_embeds + ^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py", line 392, in forward + rope_cos = rope_cos[position_ids].unsqueeze(2) # [bs, seq_len, 1, dim] + ~~~~~~~~^^^^^^^^^^^^^^ +IndexError: index 239254133933015924 is out of bounds for dimension 0 with size 11 +{"index": 73, "model": "Alibaba-NLP/gte-large-en-v1.5", "revision": "104333d6af6f97649377c2afbde10a7704870c7b", "trending_rank": 73, "downloads_rank": 27, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": true, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:46:09.987170+00:00", "physical_visible_core": "8", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 3.194855031557381, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "status": "error", "stage": "cpu_inference", "error_type": "IndexError", "error": "index 239254133933015924 is out of bounds for dimension 0 with size 11", "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/073/run.py\", line 63, in \n stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/073/run.py\", line 58, in score\n q=model.encode_query([query],batch_size=4,show_progress_bar=False,**kw)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 370, in encode_query\n return self.encode(\n ~~~~~~~~~~~^\n inputs=inputs,\n ^^^^^^^^^^^^^^\n ...<14 lines>...\n **kwargs,\n ^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 895, in encode\n all_embeddings = self._inference(inputs, device=device, **inference_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 963, in _inference\n out_features = self(features, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 600, in forward\n input = module(input, **module_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 1647, in forward\n model_output = model_method(**filtered_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 901, in forward\n (embedding_output, attention_mask, rope_embeds, length) = self.embeddings(\n ~~~~~~~~~~~~~~~^\n unpad_inputs,\n ^^^^^^^^^^^^^\n ...<5 lines>...\n inputs_embeds=inputs_embeds\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 392, in forward\n rope_cos = rope_cos[position_ids].unsqueeze(2) # [bs, seq_len, 1, dim]\n ~~~~~~~~^^^^^^^^^^^^^^\nIndexError: index 239254133933015924 is out of bounds for dimension 0 with size 11\n", "result": "FAIL(forward)", "total_seconds": 11.818632579408586} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/075.log b/validation/sentence-transformers/2026-11-03-top100/logs/075.log new file mode 100644 index 0000000000000000000000000000000000000000..d6cdf6a7a42eede98a2724ed5d4a03217a4115aa --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/075.log @@ -0,0 +1,62 @@ +httpx.HTTPStatusError: Client error '403 Forbidden' for url 'https://huggingface.co/nvidia/NV-Embed-v1/resolve/2e8b322e2b738a383dae0dde5fa19e0b28a5bb11/modules.json' +For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/403 + +The above exception was the direct cause of the following exception: + +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/075/run.py", line 50, in + model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']}) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 193, in __init__ + super().__init__( + ~~~~~~~~~~~~~~~~^ + model_name_or_path=model_name_or_path, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ...<13 lines>... + default_prompt_name=default_prompt_name, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 256, in __init__ + modules, self.module_kwargs = self._load_modules( + ~~~~~~~~~~~~~~~~~~^ + model_name_or_path, + ^^^^^^^^^^^^^^^^^^^ + ...<7 lines>... + config_kwargs=config_kwargs, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 1190, in _load_modules + modules_json_path = load_file_path( + model_name_or_path, + ...<4 lines>... + local_files_only=local_files_only, + ) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/file_io.py", line 208, in load_file_path + return hf_hub_download( + model_name_or_path, + ...<6 lines>... + local_files_only=local_files_only, + ) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/utils/_validators.py", line 89, in _inner_fn + return fn(*args, **kwargs) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/utils/_http.py", line 266, in _inner + return fn(*args, **kwargs) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py", line 1047, in hf_hub_download + return _hf_hub_download_to_cache_dir( + # Destination + ...<15 lines>... + dry_run=dry_run, + ) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py", line 1194, in _hf_hub_download_to_cache_dir + _raise_on_head_call_error(head_call_error, force_download, local_files_only) + ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py", line 1953, in _raise_on_head_call_error + raise head_call_error +huggingface_hub.errors.GatedRepoError: 403 Client Error. (Request ID: Root=1-6aea01d2-3206be3e053d1684092fc8e7;1a302a3a-37c9-46e0-94a8-99f64b2e4802) + +Cannot access gated repo for url https://huggingface.co/nvidia/NV-Embed-v1/resolve/2e8b322e2b738a383dae0dde5fa19e0b28a5bb11/modules.json. +Access to model nvidia/NV-Embed-v1 is restricted and you are not in the authorized list. Visit https://huggingface.co/nvidia/NV-Embed-v1 to ask for access. +{"index": 75, "model": "nvidia/NV-Embed-v1", "revision": "2e8b322e2b738a383dae0dde5fa19e0b28a5bb11", "trending_rank": 75, "downloads_rank": null, "class": "SentenceTransformer", "dtype": "bfloat16", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:46:17.899843+00:00", "physical_visible_core": "4", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "status": "error", "stage": "load_cpu", "error_type": "GatedRepoError", "error": "403 Client Error. (Request ID: Root=1-6aea01d2-3206be3e053d1684092fc8e7;1a302a3a-37c9-46e0-94a8-99f64b2e4802)\n\nCannot access gated repo for url https://huggingface.co/nvidia/NV-Embed-v1/resolve/2e8b322e2b738a383dae0dde5fa19e0b28a5bb11/modules.json.\nAccess to model nvidia/NV-Embed-v1 is restricted and you are not in the authorized list. Visit https://huggingface.co/nvidia/NV-Embed-v1 to ask for access.", "traceback": "httpx.HTTPStatusError: Client error '403 Forbidden' for url 'https://huggingface.co/nvidia/NV-Embed-v1/resolve/2e8b322e2b738a383dae0dde5fa19e0b28a5bb11/modules.json'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/403\n\nThe above exception was the direct cause of the following exception:\n\nTraceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/075/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1190, in _load_modules\n modules_json_path = load_file_path(\n model_name_or_path,\n ...<4 lines>...\n local_files_only=local_files_only,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/file_io.py\", line 208, in load_file_path\n return hf_hub_download(\n model_name_or_path,\n ...<6 lines>...\n local_files_only=local_files_only,\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/utils/_validators.py\", line 89, in _inner_fn\n return fn(*args, **kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/utils/_http.py\", line 266, in _inner\n return fn(*args, **kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py\", line 1047, in hf_hub_download\n return _hf_hub_download_to_cache_dir(\n # Destination\n ...<15 lines>...\n dry_run=dry_run,\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py\", line 1194, in _hf_hub_download_to_cache_dir\n _raise_on_head_call_error(head_call_error, force_download, local_files_only)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py\", line 1953, in _raise_on_head_call_error\n raise head_call_error\nhuggingface_hub.errors.GatedRepoError: 403 Client Error. (Request ID: Root=1-6aea01d2-3206be3e053d1684092fc8e7;1a302a3a-37c9-46e0-94a8-99f64b2e4802)\n\nCannot access gated repo for url https://huggingface.co/nvidia/NV-Embed-v1/resolve/2e8b322e2b738a383dae0dde5fa19e0b28a5bb11/modules.json.\nAccess to model nvidia/NV-Embed-v1 is restricted and you are not in the authorized list. Visit https://huggingface.co/nvidia/NV-Embed-v1 to ask for access.\n", "result": "FAIL(load)", "total_seconds": 8.890233975835145} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/077.log b/validation/sentence-transformers/2026-11-03-top100/logs/077.log new file mode 100644 index 0000000000000000000000000000000000000000..b2569142b92d1c76de868705f2bbdf9d5dbc6e9e --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/077.log @@ -0,0 +1,6 @@ +[transformers] We found `hidden_act="gelu"` in this Gemma config. This is a legacy value of the official releases but it is meant to target the tanh approximation. Setting `hidden_act="gelu_pytorch_tanh"` instead. +CPU [0.9210729002952576, 0.9032096862792969, 0.9318515062332153, 0.9134941101074219] +2026-Nov-03 15:46:48.420935 2475124:2475124 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +{"index": 77, "model": "Jaume/gemma-2b-embeddings", "revision": "86431f65d7c3f66b2af096c61e614a2958f191f1", "trending_rank": 77, "downloads_rank": null, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:46:28.024988+00:00", "physical_visible_core": "4", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 4.274750509299338, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "embedding_devices": ["neuron:0", "neuron:0"], "cpu_scores": [0.9210729002952576, 0.9032096862792969, 0.9318515062332153, 0.9134941101074219], "cpu_seconds": 6.217862844467163, "cpu_top_document": 3, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 38.68630393128842, "neuron_scores": [0.921073317527771, 0.9032103419303894, 0.9318520426750183, 0.9134945273399353], "max_abs_error": 6.556510925292969e-07, "neuron_top_document": 3, "mars_first": false, "cpu_parity": true, "neuron_repeat_seconds": 0.15275748260319233, "repeat_max_abs_error": 0.0, "repeat_stable": true, "status": "executed", "result": "FAIL(output)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 410, "sample_interval_seconds": 0.1, "peak_bytes": 10209788025, "peak_categories": {"code": 11395752, "tensors": 10108276736, "constants": 4882449, "scratchpad": 67108864, "misc": 15922624, "dma_rings": 2201600}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 10050966144, "allocator_peak_reserved_bytes": 10108272640, "total_seconds": 68.6340330131352} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/078.log b/validation/sentence-transformers/2026-11-03-top100/logs/078.log new file mode 100644 index 0000000000000000000000000000000000000000..9efa9872604eff15123722e723f680d22ff66f1b --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/078.log @@ -0,0 +1,65 @@ +/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/configuration_utils.py:723: FutureWarning: `rope_scaling` is deprecated and will be removed in a future version. Set `rope_parameters` instead, with `rope_type` and `rope_theta` included. + warnings.warn( +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/078/run.py", line 63, in + stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1) + ~~~~~^^ + File "/tmp/neuron-top100-sweep/runs/078/run.py", line 55, in score + values=model.predict([(query,d) for d in docs],batch_size=4,convert_to_tensor=True,show_progress_bar=False) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py", line 124, in decorate_context + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 209, in wrapper + return func(self, *args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/cross_encoder/model.py", line 645, in predict + pred_scores = self._inference(inputs, device=device, **inference_kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py", line 124, in decorate_context + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/cross_encoder/model.py", line 689, in _inference + out_features = self(features, **kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 600, in forward + input = module(input, **module_kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 1647, in forward + model_output = model_method(**filtered_kwargs) + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py", line 1117, in forward + outputs = self.new( + input_ids, + ...<8 lines>... + unpad_inputs=unpad_inputs, + ) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py", line 901, in forward + (embedding_output, attention_mask, rope_embeds, length) = self.embeddings( + ~~~~~~~~~~~~~~~^ + unpad_inputs, + ^^^^^^^^^^^^^ + ...<5 lines>... + inputs_embeds=inputs_embeds + ^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py", line 392, in forward + rope_cos = rope_cos[position_ids].unsqueeze(2) # [bs, seq_len, 1, dim] + ~~~~~~~~^^^^^^^^^^^^^^ +IndexError: index 139625091826798 is out of bounds for dimension 0 with size 32 +{"index": 78, "model": "Alibaba-NLP/gte-multilingual-reranker-base", "revision": "8215cf04918ba6f7b6a62bb44238ce2953d8831c", "trending_rank": 78, "downloads_rank": null, "class": "CrossEncoder", "dtype": "float32", "attention": "sdpa", "trust_remote_code": true, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:46:48.108932+00:00", "physical_visible_core": "0", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 2.7446684883907437, "prompts": {}, "parameter_dtypes": ["torch.float32"], "status": "error", "stage": "cpu_inference", "error_type": "IndexError", "error": "index 139625091826798 is out of bounds for dimension 0 with size 32", "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/078/run.py\", line 63, in \n stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/078/run.py\", line 55, in score\n values=model.predict([(query,d) for d in docs],batch_size=4,convert_to_tensor=True,show_progress_bar=False)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 209, in wrapper\n return func(self, *args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/cross_encoder/model.py\", line 645, in predict\n pred_scores = self._inference(inputs, device=device, **inference_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/cross_encoder/model.py\", line 689, in _inference\n out_features = self(features, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 600, in forward\n input = module(input, **module_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 1647, in forward\n model_output = model_method(**filtered_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 1117, in forward\n outputs = self.new(\n input_ids,\n ...<8 lines>...\n unpad_inputs=unpad_inputs,\n )\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 901, in forward\n (embedding_output, attention_mask, rope_embeds, length) = self.embeddings(\n ~~~~~~~~~~~~~~~^\n unpad_inputs,\n ^^^^^^^^^^^^^\n ...<5 lines>...\n inputs_embeds=inputs_embeds\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 392, in forward\n rope_cos = rope_cos[position_ids].unsqueeze(2) # [bs, seq_len, 1, dim]\n ~~~~~~~~^^^^^^^^^^^^^^\nIndexError: index 139625091826798 is out of bounds for dimension 0 with size 32\n", "result": "FAIL(forward)", "total_seconds": 15.83839768357575} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/079.log b/validation/sentence-transformers/2026-11-03-top100/logs/079.log new file mode 100644 index 0000000000000000000000000000000000000000..7a15412385ea70fe040564fc14b2bef4f3012090 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/079.log @@ -0,0 +1,5 @@ +CPU [0.45112812519073486, 0.5921509265899658, 0.3681429922580719, 0.6955137848854065] +2026-Nov-03 15:47:10.573216 2480704:2480704 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +{"index": 79, "model": "akhooli/Arabic-SBERT-100K", "revision": "67199ee95d81bb10047c946b1b4268c8703b83db", "trending_rank": 79, "downloads_rank": null, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:46:59.382279+00:00", "physical_visible_core": "12", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 1.3999376483261585, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "embedding_devices": ["neuron:0", "neuron:0"], "cpu_scores": [0.45112812519073486, 0.5921509265899658, 0.3681429922580719, 0.6955137848854065], "cpu_seconds": 0.4114110991358757, "cpu_top_document": 4, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 0.4038874404504895, "neuron_scores": [0.45112812519073486, 0.5921508073806763, 0.3681427240371704, 0.6955137252807617], "max_abs_error": 2.682209014892578e-07, "neuron_top_document": 4, "mars_first": false, "cpu_parity": true, "neuron_repeat_seconds": 0.06409406755119562, "repeat_max_abs_error": 0.0, "repeat_stable": true, "status": "executed", "result": "FAIL(output)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 7, "sample_interval_seconds": 0.1, "peak_bytes": 695672385, "peak_categories": {"code": 6654512, "tensors": 606081024, "constants": 3473425, "scratchpad": 67108864, "misc": 9832960, "dma_rings": 2521600}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 587197440, "allocator_peak_reserved_bytes": 606076928, "total_seconds": 21.84079162403941} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/081.log b/validation/sentence-transformers/2026-11-03-top100/logs/081.log new file mode 100644 index 0000000000000000000000000000000000000000..67edb7cee20c351cd3f0b971498db782e7e521d2 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/081.log @@ -0,0 +1,75 @@ +[transformers] `torch_dtype` is deprecated! Use `dtype` instead! +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/081/run.py", line 50, in + model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']}) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 193, in __init__ + super().__init__( + ~~~~~~~~~~~~~~~~^ + model_name_or_path=model_name_or_path, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ...<13 lines>... + default_prompt_name=default_prompt_name, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 256, in __init__ + modules, self.module_kwargs = self._load_modules( + ~~~~~~~~~~~~~~~~~~^ + model_name_or_path, + ^^^^^^^^^^^^^^^^^^^ + ...<7 lines>... + config_kwargs=config_kwargs, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 1211, in _load_modules + return self._load_config_modules(model_name_or_path, **load_kwargs) + ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 1404, in _load_config_modules + module = module_class(model_name_or_path, **init_kwargs) + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_embeddings_hyphen_v3/ab036b023d30b4d1138c4c3bfa9f0c445ab455d6/custom_st.py", line 87, in __init__ + self.auto_model = AutoModel.from_pretrained(model_name_or_path, config=self.config, **model_args) + ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py", line 389, in from_pretrained + return model_class.from_pretrained( + ~~~~~~~~~~~~~~~~~~~~~~~~~~~^ + pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/xlm_hyphen_roberta_hyphen_flash_hyphen_implementation/bd55a5ec8e6c0fb1d6c26efb4b6a4a74ce8a88d3/modeling_lora.py", line 338, in from_pretrained + return super().from_pretrained( + ~~~~~~~~~~~~~~~~~~~~~~~^ + pretrained_model_name_or_path, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ...<9 lines>... + **kwargs, + ^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/xlm_hyphen_roberta_hyphen_flash_hyphen_implementation/bd55a5ec8e6c0fb1d6c26efb4b6a4a74ce8a88d3/modeling_xlm_roberta.py", line 442, in from_pretrained + return super().from_pretrained(*args, **kwargs) + ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py", line 4356, in from_pretrained + loading_info = cls._finalize_model_loading(model, load_config, loading_info) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py", line 4524, in _finalize_model_loading + model._move_missing_keys_from_meta_to_device( + ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ + loading_info.missing_and_mismatched(), + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ...<2 lines>... + load_config.hf_quantizer, + ^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py", line 4781, in _move_missing_keys_from_meta_to_device + for key in missing_keys - self.all_tied_weights_keys.keys(): + ^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1972, in __getattr__ + raise AttributeError( + f"'{type(self).__name__}' object has no attribute '{name}'" + ) +AttributeError: 'XLMRobertaLoRA' object has no attribute 'all_tied_weights_keys'. Did you mean: '_tied_weights_keys'? +{"index": 81, "model": "jinaai/jina-embeddings-v3", "revision": "ab036b023d30b4d1138c4c3bfa9f0c445ab455d6", "trending_rank": 81, "downloads_rank": 32, "class": "SentenceTransformer", "dtype": "float32", "attention": "eager", "trust_remote_code": true, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:47:35.211638+00:00", "physical_visible_core": "12", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "status": "error", "stage": "load_cpu", "error_type": "AttributeError", "error": "'XLMRobertaLoRA' object has no attribute 'all_tied_weights_keys'", "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/081/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1404, in _load_config_modules\n module = module_class(model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_embeddings_hyphen_v3/ab036b023d30b4d1138c4c3bfa9f0c445ab455d6/custom_st.py\", line 87, in __init__\n self.auto_model = AutoModel.from_pretrained(model_name_or_path, config=self.config, **model_args)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 389, in from_pretrained\n return model_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/xlm_hyphen_roberta_hyphen_flash_hyphen_implementation/bd55a5ec8e6c0fb1d6c26efb4b6a4a74ce8a88d3/modeling_lora.py\", line 338, in from_pretrained\n return super().from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<9 lines>...\n **kwargs,\n ^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/xlm_hyphen_roberta_hyphen_flash_hyphen_implementation/bd55a5ec8e6c0fb1d6c26efb4b6a4a74ce8a88d3/modeling_xlm_roberta.py\", line 442, in from_pretrained\n return super().from_pretrained(*args, **kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4356, in from_pretrained\n loading_info = cls._finalize_model_loading(model, load_config, loading_info)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4524, in _finalize_model_loading\n model._move_missing_keys_from_meta_to_device(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n loading_info.missing_and_mismatched(),\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<2 lines>...\n load_config.hf_quantizer,\n ^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4781, in _move_missing_keys_from_meta_to_device\n for key in missing_keys - self.all_tied_weights_keys.keys():\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1972, in __getattr__\n raise AttributeError(\n f\"'{type(self).__name__}' object has no attribute '{name}'\"\n )\nAttributeError: 'XLMRobertaLoRA' object has no attribute 'all_tied_weights_keys'. Did you mean: '_tied_weights_keys'?\n", "result": "FAIL(load)", "total_seconds": 19.574221355840564} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/083.log b/validation/sentence-transformers/2026-11-03-top100/logs/083.log new file mode 100644 index 0000000000000000000000000000000000000000..dc9869d8aaa61098e637b67eaf31d43e5fe01295 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/083.log @@ -0,0 +1,5 @@ +CPU [0.20963680744171143, 0.5245946049690247, 0.4401358366012573, 0.585011899471283] +2026-Nov-03 15:47:52.897933 2508243:2508243 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +{"index": 83, "model": "meandyou200175/phobert-finetune", "revision": "26e5f91ad1eb94b0af813021a2b7097ae4ba228e", "trending_rank": 83, "downloads_rank": null, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:47:38.793972+00:00", "physical_visible_core": "4", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 1.9071867559105158, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "embedding_devices": ["neuron:0", "neuron:0"], "cpu_scores": [0.20963680744171143, 0.5245946049690247, 0.4401358366012573, 0.585011899471283], "cpu_seconds": 0.2299742652103305, "cpu_top_document": 4, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 43.493039570748806, "neuron_scores": [0.20963667333126068, 0.5245950222015381, 0.44013622403144836, 0.5850120782852173], "max_abs_error": 4.172325134277344e-07, "neuron_top_document": 4, "mars_first": false, "cpu_parity": true, "neuron_repeat_seconds": 0.05636020377278328, "repeat_max_abs_error": 0.0, "repeat_stable": true, "status": "executed", "result": "FAIL(output)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 437, "sample_interval_seconds": 0.1, "peak_bytes": 701178529, "peak_categories": {"code": 7318992, "tensors": 608178176, "constants": 3440657, "scratchpad": 67108864, "misc": 11850688, "dma_rings": 3281152}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 586056448, "allocator_peak_reserved_bytes": 608174080, "total_seconds": 64.42325356975198} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/089.log b/validation/sentence-transformers/2026-11-03-top100/logs/089.log new file mode 100644 index 0000000000000000000000000000000000000000..8b55c1cea9c7d1b4c33676173e0412f3a1024891 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/089.log @@ -0,0 +1,21 @@ +[transformers] Qwen2_5_VLModel LOAD REPORT from: vidore/colqwen2.5-base +Key | Status | | +------------------------+------------+--+- +custom_text_proj.weight | UNEXPECTED | | +custom_text_proj.bias | UNEXPECTED | | + +Notes: +- UNEXPECTED: can be ignored when loading from different task/architecture; not ok if you expect identical arch. +[transformers] Qwen2_5_VLModel LOAD REPORT from: vidore/colqwen2.5-v0.2 +Key | Status | | +---------------------------------------+------------+--+- +custom_text_proj.lora_A.default.weight | UNEXPECTED | | +custom_text_proj.lora_B.default.weight | UNEXPECTED | | + +Notes: +- UNEXPECTED: can be ignored when loading from different task/architecture; not ok if you expect identical arch. +CPU [10.587596893310547, 15.282479286193848, 11.481404304504395, 15.91786003112793] +2026-Nov-03 15:49:49.360524 2553666:2553666 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +{"index": 89, "model": "vidore/colqwen2.5-v0.2", "revision": "dcbe8d9cede518bce830488364ba0e40c873645b", "trending_rank": 89, "downloads_rank": null, "class": "MultiVectorEncoder", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:49:04.100500+00:00", "physical_visible_core": "0", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 30.20843593403697, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "embedding_devices": ["neuron:0", "neuron:0"], "cpu_scores": [10.587596893310547, 15.282479286193848, 11.481404304504395, 15.91786003112793], "cpu_seconds": 2.5352238938212395, "cpu_top_document": 4, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 78.56518525443971, "neuron_scores": [10.587594032287598, 15.282479286193848, 11.481398582458496, 15.917861938476562], "max_abs_error": 5.7220458984375e-06, "neuron_top_document": 4, "mars_first": false, "cpu_parity": true, "neuron_repeat_seconds": 0.9287767671048641, "repeat_max_abs_error": 0.0, "repeat_stable": true, "status": "executed", "result": "FAIL(output)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 811, "sample_interval_seconds": 0.1, "peak_bytes": 15556525689, "peak_categories": {"code": 13058680, "tensors": 15437139968, "constants": 6002945, "scratchpad": 67108864, "misc": 22477824, "dma_rings": 10737408}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 15333365888, "allocator_peak_reserved_bytes": 15437135872, "total_seconds": 134.7353895958513} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/108.log b/validation/sentence-transformers/2026-11-03-top100/logs/108.log new file mode 100644 index 0000000000000000000000000000000000000000..e379e146dd1e7eb3ea4905e8416a1a87aec864ae --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/108.log @@ -0,0 +1,64 @@ +[transformers] `torch_dtype` is deprecated! Use `dtype` instead! +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/108/run.py", line 50, in + model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']}) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 163, in wrapper + return func(self, *args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/cross_encoder/model.py", line 200, in __init__ + super().__init__( + ~~~~~~~~~~~~~~~~^ + model_name_or_path=model_name_or_path, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ...<13 lines>... + default_prompt_name=default_prompt_name, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 256, in __init__ + modules, self.module_kwargs = self._load_modules( + ~~~~~~~~~~~~~~~~~~^ + model_name_or_path, + ^^^^^^^^^^^^^^^^^^^ + ...<7 lines>... + config_kwargs=config_kwargs, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 1200, in _load_modules + return self._load_default_modules(model_name_or_path, **load_kwargs) + ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/cross_encoder/model.py", line 337, in _load_default_modules + transformer_model = Transformer( + model_name_or_path, + ...<5 lines>... + backend=self.backend, + ) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 92, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 855, in __init__ + self.model = self._load_model( + ~~~~~~~~~~~~~~~~^ + model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 2343, in _load_model + return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs) + ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py", line 381, in from_pretrained + model_class = get_class_from_dynamic_module( + class_ref, pretrained_model_name_or_path, code_revision=code_revision, **hub_kwargs, **kwargs + ) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py", line 625, in get_class_from_dynamic_module + return get_class_in_module(class_name, final_module, force_reload=force_download) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py", line 309, in get_class_in_module + module_spec.loader.exec_module(module) + ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^ + File "", line 759, in exec_module + File "", line 491, in _call_with_frames_removed + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_reranker_hyphen_v2_hyphen_base_hyphen_multilingual/9cfeff2df7d40d1b78e75e5e9cebec92a99813c9/modeling_xlm_roberta.py", line 44, in + from .embedding import XLMRobertaEmbeddings + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_reranker_hyphen_v2_hyphen_base_hyphen_multilingual/9cfeff2df7d40d1b78e75e5e9cebec92a99813c9/embedding.py", line 11, in + from transformers.models.xlm_roberta.modeling_xlm_roberta import create_position_ids_from_input_ids +ImportError: cannot import name 'create_position_ids_from_input_ids' from 'transformers.models.xlm_roberta.modeling_xlm_roberta' (/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/xlm_roberta/modeling_xlm_roberta.py) +{"index": 108, "model": "jinaai/jina-reranker-v2-base-multilingual", "revision": "9cfeff2df7d40d1b78e75e5e9cebec92a99813c9", "trending_rank": null, "downloads_rank": 29, "class": "CrossEncoder", "dtype": "float32", "attention": "sdpa", "trust_remote_code": true, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:52:03.168120+00:00", "physical_visible_core": "4", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "status": "error", "stage": "load_cpu", "error_type": "ImportError", "error": "cannot import name 'create_position_ids_from_input_ids' from 'transformers.models.xlm_roberta.modeling_xlm_roberta' (/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/xlm_roberta/modeling_xlm_roberta.py)", "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/108/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 163, in wrapper\n return func(self, *args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/cross_encoder/model.py\", line 200, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1200, in _load_modules\n return self._load_default_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/cross_encoder/model.py\", line 337, in _load_default_modules\n transformer_model = Transformer(\n model_name_or_path,\n ...<5 lines>...\n backend=self.backend,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 855, in __init__\n self.model = self._load_model(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2343, in _load_model\n return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 381, in from_pretrained\n model_class = get_class_from_dynamic_module(\n class_ref, pretrained_model_name_or_path, code_revision=code_revision, **hub_kwargs, **kwargs\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 625, in get_class_from_dynamic_module\n return get_class_in_module(class_name, final_module, force_reload=force_download)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 309, in get_class_in_module\n module_spec.loader.exec_module(module)\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^\n File \"\", line 759, in exec_module\n File \"\", line 491, in _call_with_frames_removed\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_reranker_hyphen_v2_hyphen_base_hyphen_multilingual/9cfeff2df7d40d1b78e75e5e9cebec92a99813c9/modeling_xlm_roberta.py\", line 44, in \n from .embedding import XLMRobertaEmbeddings\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_reranker_hyphen_v2_hyphen_base_hyphen_multilingual/9cfeff2df7d40d1b78e75e5e9cebec92a99813c9/embedding.py\", line 11, in \n from transformers.models.xlm_roberta.modeling_xlm_roberta import create_position_ids_from_input_ids\nImportError: cannot import name 'create_position_ids_from_input_ids' from 'transformers.models.xlm_roberta.modeling_xlm_roberta' (/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/xlm_roberta/modeling_xlm_roberta.py)\n", "result": "FAIL(load)", "total_seconds": 10.194885298609734} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/112.log b/validation/sentence-transformers/2026-11-03-top100/logs/112.log new file mode 100644 index 0000000000000000000000000000000000000000..61bdd6d7c8876657bc786cdd8de54464f494b99d --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/112.log @@ -0,0 +1,18 @@ +CPU [18.622793197631836, 25.37649154663086, 24.276288986206055, 23.726768493652344] +2026-Nov-03 15:52:45.685760 2659064:2659064 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/112/run.py", line 69, in + stage='neuron_inference';t=time.monotonic();actual=score();r['score_device']=str(actual.device) + ~~~~~^^ + File "/tmp/neuron-top100-sweep/runs/112/run.py", line 61, in score + values=model.similarity(q,d) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 1072, in similarity + return self._similarity(embeddings1, embeddings2) + ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/similarity.py", line 115, in dot_score + return torch.mm(a, b.transpose(0, 1)).to_dense() + ~~~~~~~~~~~^^^^^^ +RuntimeError: Inference tensors do not track version counter. +{"index": 112, "model": "sentence-transformers/multi-qa-mpnet-base-dot-v1", "revision": "17997f24dca0df1a4fed68894fb0e1e133e60482", "trending_rank": null, "downloads_rank": 34, "class": "SentenceTransformer", "dtype": "float32", "attention": "eager", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:52:37.157163+00:00", "physical_visible_core": "8", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 0.9057708652690053, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "embedding_devices": ["neuron:0", "neuron:0"], "cpu_scores": [18.622793197631836, 25.37649154663086, 24.276288986206055, 23.726768493652344], "cpu_seconds": 0.13503286056220531, "cpu_top_document": 2, "model_device": "neuron:0", "status": "error", "stage": "neuron_inference", "error_type": "RuntimeError", "error": "Inference tensors do not track version counter.", "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/112/run.py\", line 69, in \n stage='neuron_inference';t=time.monotonic();actual=score();r['score_device']=str(actual.device)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/112/run.py\", line 61, in score\n values=model.similarity(q,d)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 1072, in similarity\n return self._similarity(embeddings1, embeddings2)\n ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/similarity.py\", line 115, in dot_score\n return torch.mm(a, b.transpose(0, 1)).to_dense()\n ~~~~~~~~~~~^^^^^^\nRuntimeError: Inference tensors do not track version counter.\n", "result": "FAIL(forward)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 9, "sample_interval_seconds": 0.1, "peak_bytes": 602256101, "peak_categories": {"code": 8931864, "tensors": 501223424, "constants": 3440653, "scratchpad": 67108864, "misc": 17067456, "dma_rings": 4483840}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 481360448, "allocator_peak_reserved_bytes": 501219328, "total_seconds": 16.84018260613084} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/113.log b/validation/sentence-transformers/2026-11-03-top100/logs/113.log new file mode 100644 index 0000000000000000000000000000000000000000..fcc669387deb7402dce5b5234893efec55c38397 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/113.log @@ -0,0 +1,5 @@ +CPU [0.4128049910068512, 0.6425286531448364, 0.671911358833313, 0.6263707876205444] +2026-Nov-03 15:52:38.469930 2658598:2658598 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +{"index": 113, "model": "sentence-transformers/paraphrase-MiniLM-L6-v2", "revision": "c9a2bfebc254878aee8c3aca9e6844d5bbb102d1", "trending_rank": null, "downloads_rank": 35, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:52:29.729330+00:00", "physical_visible_core": "0", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 0.8102488135918975, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "embedding_devices": ["neuron:0", "neuron:0"], "cpu_scores": [0.4128049910068512, 0.6425286531448364, 0.671911358833313, 0.6263707876205444], "cpu_seconds": 0.053661770187318325, "cpu_top_document": 3, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 0.3346906406804919, "neuron_scores": [0.4128049612045288, 0.6425285339355469, 0.671911358833313, 0.6263706684112549], "max_abs_error": 1.1920928955078125e-07, "neuron_top_document": 3, "mars_first": false, "cpu_parity": true, "neuron_repeat_seconds": 0.03071187622845173, "repeat_max_abs_error": 0.0, "repeat_stable": true, "status": "executed", "result": "FAIL(output)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 5, "sample_interval_seconds": 0.1, "peak_bytes": 224453665, "peak_categories": {"code": 6359632, "tensors": 136318976, "constants": 3047441, "scratchpad": 67108864, "misc": 8984256, "dma_rings": 2634496}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 97223040, "allocator_peak_reserved_bytes": 136314880, "total_seconds": 16.178581200540066} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/114.log b/validation/sentence-transformers/2026-11-03-top100/logs/114.log new file mode 100644 index 0000000000000000000000000000000000000000..974a0b53148f296d107ce3306a6ab15987d94e62 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/114.log @@ -0,0 +1,59 @@ +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/114/run.py", line 50, in + model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']}) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 193, in __init__ + super().__init__( + ~~~~~~~~~~~~~~~~^ + model_name_or_path=model_name_or_path, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ...<13 lines>... + default_prompt_name=default_prompt_name, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 256, in __init__ + modules, self.module_kwargs = self._load_modules( + ~~~~~~~~~~~~~~~~~~^ + model_name_or_path, + ^^^^^^^^^^^^^^^^^^^ + ...<7 lines>... + config_kwargs=config_kwargs, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 1211, in _load_modules + return self._load_config_modules(model_name_or_path, **load_kwargs) + ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 1431, in _load_config_modules + module = module_class.load( + model_name_or_path, + ...<12 lines>... + **extra_load_kwargs, + ) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 2641, in load + return cls(model_name_or_path=model_name_or_path, **init_kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 92, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 839, in __init__ + config, is_peft_model = self._load_config(model_name_or_path, backend, config_kwargs) + ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 2259, in _load_config + return AutoConfig.from_pretrained(model_name_or_path, **config_kwargs), False + ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/configuration_auto.py", line 422, in from_pretrained + config_class = get_class_from_dynamic_module( + class_ref, pretrained_model_name_or_path, code_revision=code_revision, **kwargs + ) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py", line 625, in get_class_from_dynamic_module + return get_class_in_module(class_name, final_module, force_reload=force_download) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py", line 309, in get_class_in_module + module_spec.loader.exec_module(module) + ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^ + File "", line 759, in exec_module + File "", line 491, in _call_with_frames_removed + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_bert_hyphen_implementation/f3ec4cf7de7e561007f27c9efc7148b0bd713f81/configuration_bert.py", line 22, in + from transformers.onnx import OnnxConfig +ModuleNotFoundError: No module named 'transformers.onnx' +{"index": 114, "model": "jinaai/jina-embeddings-v2-small-en", "revision": "44e7d1d6caec8c883c2d4b207588504d519788d0", "trending_rank": null, "downloads_rank": 38, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": true, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:52:45.768912+00:00", "physical_visible_core": "4", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "status": "error", "stage": "load_cpu", "error_type": "ModuleNotFoundError", "error": "No module named 'transformers.onnx'", "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/114/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 839, in __init__\n config, is_peft_model = self._load_config(model_name_or_path, backend, config_kwargs)\n ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2259, in _load_config\n return AutoConfig.from_pretrained(model_name_or_path, **config_kwargs), False\n ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/configuration_auto.py\", line 422, in from_pretrained\n config_class = get_class_from_dynamic_module(\n class_ref, pretrained_model_name_or_path, code_revision=code_revision, **kwargs\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 625, in get_class_from_dynamic_module\n return get_class_in_module(class_name, final_module, force_reload=force_download)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 309, in get_class_in_module\n module_spec.loader.exec_module(module)\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^\n File \"\", line 759, in exec_module\n File \"\", line 491, in _call_with_frames_removed\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_bert_hyphen_implementation/f3ec4cf7de7e561007f27c9efc7148b0bd713f81/configuration_bert.py\", line 22, in \n from transformers.onnx import OnnxConfig\nModuleNotFoundError: No module named 'transformers.onnx'\n", "result": "FAIL(load)", "total_seconds": 8.320869617164135} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/116.log b/validation/sentence-transformers/2026-11-03-top100/logs/116.log new file mode 100644 index 0000000000000000000000000000000000000000..ea9b99c62ca873b06e7c7d3781d38ecb0ba66f1e --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/116.log @@ -0,0 +1,5 @@ +CPU [0.3725859224796295, 0.5596363544464111, 0.475629597902298, 0.6078733205795288] +2026-Nov-03 15:53:01.715051 2661367:2661367 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +{"index": 116, "model": "jhgan/ko-sroberta-multitask", "revision": "8fca7c9c98c26599be0e14b9916b11a756a26f19", "trending_rank": null, "downloads_rank": 42, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:52:52.178170+00:00", "physical_visible_core": "12", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 1.2254862170666456, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "embedding_devices": ["neuron:0", "neuron:0"], "cpu_scores": [0.3725859224796295, 0.5596363544464111, 0.475629597902298, 0.6078733205795288], "cpu_seconds": 0.2339512938633561, "cpu_top_document": 4, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 46.99652501568198, "neuron_scores": [0.3725859224796295, 0.5596362352371216, 0.47562968730926514, 0.6078732013702393], "max_abs_error": 1.1920928955078125e-07, "neuron_top_document": 4, "mars_first": false, "cpu_parity": true, "neuron_repeat_seconds": 0.04155152477324009, "repeat_max_abs_error": 0.0, "repeat_stable": true, "status": "executed", "result": "FAIL(output)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 472, "sample_interval_seconds": 0.1, "peak_bytes": 604724833, "peak_categories": {"code": 7286160, "tensors": 511709184, "constants": 3866641, "scratchpad": 67108864, "misc": 12000704, "dma_rings": 2753280}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 492647808, "allocator_peak_reserved_bytes": 511705088, "total_seconds": 62.91153274290264} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/122.log b/validation/sentence-transformers/2026-11-03-top100/logs/122.log new file mode 100644 index 0000000000000000000000000000000000000000..4afede4233d4d6dac4f6b3235ca9a7eec9b6e837 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/122.log @@ -0,0 +1,5 @@ +CPU [0.5895186066627502, 0.6596499085426331, 0.6842697262763977, 0.7085862755775452] +2026-Nov-03 15:53:40.215912 2667583:2667583 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +{"index": 122, "model": "sentence-transformers-testing/stsb-bert-tiny-safetensors", "revision": "f3cb857cba53019a20df283396bcca179cf051a4", "trending_rank": null, "downloads_rank": 49, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:53:27.210620+00:00", "physical_visible_core": "0", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 0.339894263073802, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "embedding_devices": ["neuron:0", "neuron:0"], "cpu_scores": [0.5895186066627502, 0.6596499085426331, 0.6842697262763977, 0.7085862755775452], "cpu_seconds": 0.01665687095373869, "cpu_top_document": 4, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 35.90269974432886, "neuron_scores": [0.5895187258720398, 0.6596502065658569, 0.6842698454856873, 0.7085865139961243], "max_abs_error": 2.980232238769531e-07, "neuron_top_document": 4, "mars_first": false, "cpu_parity": true, "neuron_repeat_seconds": 0.01644056662917137, "repeat_max_abs_error": 0.0, "repeat_stable": true, "status": "executed", "result": "FAIL(output)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 360, "sample_interval_seconds": 0.1, "peak_bytes": 108670225, "peak_categories": {"code": 6199232, "tensors": 20975616, "constants": 2523153, "scratchpad": 67108864, "misc": 9350720, "dma_rings": 2512640}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 19238400, "allocator_peak_reserved_bytes": 20971520, "total_seconds": 57.112566504627466} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/123.log b/validation/sentence-transformers/2026-11-03-top100/logs/123.log new file mode 100644 index 0000000000000000000000000000000000000000..24121a84ee4c92a11f35286894ee876e7d9d8568 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/123.log @@ -0,0 +1,72 @@ +/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/configuration_utils.py:723: FutureWarning: `rope_scaling` is deprecated and will be removed in a future version. Set `rope_parameters` instead, with `rope_type` and `rope_theta` included. + warnings.warn( +[transformers] NewModel LOAD REPORT from: Alibaba-NLP/gte-multilingual-base +Key | Status | | +------------------+------------+--+- +classifier.weight | UNEXPECTED | | +classifier.bias | UNEXPECTED | | + +Notes: +- UNEXPECTED: can be ignored when loading from different task/architecture; not ok if you expect identical arch. +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/123/run.py", line 63, in + stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1) + ~~~~~^^ + File "/tmp/neuron-top100-sweep/runs/123/run.py", line 58, in score + q=model.encode_query([query],batch_size=4,show_progress_bar=False,**kw) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 370, in encode_query + return self.encode( + ~~~~~~~~~~~^ + inputs=inputs, + ^^^^^^^^^^^^^^ + ...<14 lines>... + **kwargs, + ^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py", line 124, in decorate_context + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 895, in encode + all_embeddings = self._inference(inputs, device=device, **inference_kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py", line 124, in decorate_context + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 963, in _inference + out_features = self(features, **kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 600, in forward + input = module(input, **module_kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 1647, in forward + model_output = model_method(**filtered_kwargs) + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py", line 901, in forward + (embedding_output, attention_mask, rope_embeds, length) = self.embeddings( + ~~~~~~~~~~~~~~~^ + unpad_inputs, + ^^^^^^^^^^^^^ + ...<5 lines>... + inputs_embeds=inputs_embeds + ^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py", line 392, in forward + rope_cos = rope_cos[position_ids].unsqueeze(2) # [bs, seq_len, 1, dim] + ~~~~~~~~^^^^^^^^^^^^^^ +IndexError: index 670466312 is out of bounds for dimension 0 with size 11 +{"index": 123, "model": "Alibaba-NLP/gte-multilingual-base", "revision": "9bbca17d9273fd0d03d5725c7a4b0f6b45142062", "trending_rank": null, "downloads_rank": 50, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": true, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:53:34.948327+00:00", "physical_visible_core": "8", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 2.7565125236287713, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "status": "error", "stage": "cpu_inference", "error_type": "IndexError", "error": "index 670466312 is out of bounds for dimension 0 with size 11", "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/123/run.py\", line 63, in \n stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/123/run.py\", line 58, in score\n q=model.encode_query([query],batch_size=4,show_progress_bar=False,**kw)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 370, in encode_query\n return self.encode(\n ~~~~~~~~~~~^\n inputs=inputs,\n ^^^^^^^^^^^^^^\n ...<14 lines>...\n **kwargs,\n ^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 895, in encode\n all_embeddings = self._inference(inputs, device=device, **inference_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 963, in _inference\n out_features = self(features, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 600, in forward\n input = module(input, **module_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 1647, in forward\n model_output = model_method(**filtered_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 901, in forward\n (embedding_output, attention_mask, rope_embeds, length) = self.embeddings(\n ~~~~~~~~~~~~~~~^\n unpad_inputs,\n ^^^^^^^^^^^^^\n ...<5 lines>...\n inputs_embeds=inputs_embeds\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 392, in forward\n rope_cos = rope_cos[position_ids].unsqueeze(2) # [bs, seq_len, 1, dim]\n ~~~~~~~~^^^^^^^^^^^^^^\nIndexError: index 670466312 is out of bounds for dimension 0 with size 11\n", "result": "FAIL(forward)", "total_seconds": 10.929977044463158} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/129.log b/validation/sentence-transformers/2026-11-03-top100/logs/129.log new file mode 100644 index 0000000000000000000000000000000000000000..74add8e99cc434b17a6430b2d3eae72681c6f095 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/129.log @@ -0,0 +1,53 @@ +/home/jingyahuang/.cache/huggingface/modules/transformers_modules/nomic_hyphen_ai/nomic_hyphen_bert_hyphen_2048/7710840340a098cfb869c4f65e87cf2b1b70caca/modeling_hf_nomic_bert.py:1634: UserWarning: Install Nomic's megablocks fork for better speed: `pip install git+https://github.com/nomic-ai/megablocks.git` + warnings.warn("Install Nomic's megablocks fork for better speed: " + +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/129/run.py", line 63, in + stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1) + ~~~~~^^ + File "/tmp/neuron-top100-sweep/runs/129/run.py", line 58, in score + q=model.encode_query([query],batch_size=4,show_progress_bar=False,**kw) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 370, in encode_query + return self.encode( + ~~~~~~~~~~~^ + inputs=inputs, + ^^^^^^^^^^^^^^ + ...<14 lines>... + **kwargs, + ^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py", line 124, in decorate_context + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 895, in encode + all_embeddings = self._inference(inputs, device=device, **inference_kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py", line 124, in decorate_context + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 963, in _inference + out_features = self(features, **kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 600, in forward + input = module(input, **module_kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 1647, in forward + model_output = model_method(**filtered_kwargs) + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/nomic_hyphen_ai/nomic_hyphen_bert_hyphen_2048/7710840340a098cfb869c4f65e87cf2b1b70caca/modeling_hf_nomic_bert.py", line 1914, in forward + attention_mask = self.get_extended_attention_mask(attention_mask, hidden_states.shape[:-1]) + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1972, in __getattr__ + raise AttributeError( + f"'{type(self).__name__}' object has no attribute '{name}'" + ) +AttributeError: 'NomicBertModel' object has no attribute 'get_extended_attention_mask' +{"index": 129, "model": "nomic-ai/nomic-embed-text-v2-moe", "revision": "1066b6599d099fbb93dfcb64f9c37a7c9e503e85", "trending_rank": null, "downloads_rank": 58, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": true, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:54:25.528812+00:00", "physical_visible_core": "4", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 6.00257970392704, "prompts": {"query": "search_query: ", "document": "", "passage": "search_document: ", "Classification": "classification: ", "MultilabelClassification": "classification: ", "Clustering": "clustering: ", "PairClassification": "classification: ", "STS": "classification: ", "Summarization": "classification: ", "Speed": "search_document: "}, "parameter_dtypes": ["torch.float32"], "status": "error", "stage": "cpu_inference", "error_type": "AttributeError", "error": "'NomicBertModel' object has no attribute 'get_extended_attention_mask'", "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/129/run.py\", line 63, in \n stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/129/run.py\", line 58, in score\n q=model.encode_query([query],batch_size=4,show_progress_bar=False,**kw)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 370, in encode_query\n return self.encode(\n ~~~~~~~~~~~^\n inputs=inputs,\n ^^^^^^^^^^^^^^\n ...<14 lines>...\n **kwargs,\n ^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 895, in encode\n all_embeddings = self._inference(inputs, device=device, **inference_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 963, in _inference\n out_features = self(features, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 600, in forward\n input = module(input, **module_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 1647, in forward\n model_output = model_method(**filtered_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/nomic_hyphen_ai/nomic_hyphen_bert_hyphen_2048/7710840340a098cfb869c4f65e87cf2b1b70caca/modeling_hf_nomic_bert.py\", line 1914, in forward\n attention_mask = self.get_extended_attention_mask(attention_mask, hidden_states.shape[:-1])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1972, in __getattr__\n raise AttributeError(\n f\"'{type(self).__name__}' object has no attribute '{name}'\"\n )\nAttributeError: 'NomicBertModel' object has no attribute 'get_extended_attention_mask'\n", "result": "FAIL(forward)", "total_seconds": 13.943258575163782} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/137.log b/validation/sentence-transformers/2026-11-03-top100/logs/137.log new file mode 100644 index 0000000000000000000000000000000000000000..43c0713bca72c540a47b0585dd01afd5c65f0f31 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/137.log @@ -0,0 +1,18 @@ +CPU [163.48626708984375, 172.62042236328125, 169.48434448242188, 169.65316772460938] +2026-Nov-03 15:55:20.166982 2695042:2695042 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/137/run.py", line 69, in + stage='neuron_inference';t=time.monotonic();actual=score();r['score_device']=str(actual.device) + ~~~~~^^ + File "/tmp/neuron-top100-sweep/runs/137/run.py", line 61, in score + values=model.similarity(q,d) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 1072, in similarity + return self._similarity(embeddings1, embeddings2) + ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/similarity.py", line 115, in dot_score + return torch.mm(a, b.transpose(0, 1)).to_dense() + ~~~~~~~~~~~^^^^^^ +RuntimeError: Inference tensors do not track version counter. +{"index": 137, "model": "sentence-transformers/msmarco-bert-base-dot-v5", "revision": "dbf04e3911e5b11c887fe563d3f2479f81c4415f", "trending_rank": null, "downloads_rank": 68, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:55:09.237654+00:00", "physical_visible_core": "0", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 1.3280827356502414, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "embedding_devices": ["neuron:0", "neuron:0"], "cpu_scores": [163.48626708984375, 172.62042236328125, 169.48434448242188, 169.65316772460938], "cpu_seconds": 0.12728324253112078, "cpu_top_document": 2, "model_device": "neuron:0", "status": "error", "stage": "neuron_inference", "error_type": "RuntimeError", "error": "Inference tensors do not track version counter.", "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/137/run.py\", line 69, in \n stage='neuron_inference';t=time.monotonic();actual=score();r['score_device']=str(actual.device)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/137/run.py\", line 61, in score\n values=model.similarity(q,d)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 1072, in similarity\n return self._similarity(embeddings1, embeddings2)\n ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/similarity.py\", line 115, in dot_score\n return torch.mm(a, b.transpose(0, 1)).to_dense()\n ~~~~~~~~~~~^^^^^^\nRuntimeError: Inference tensors do not track version counter.\n", "result": "FAIL(forward)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 6, "sample_interval_seconds": 0.1, "peak_bytes": 588585921, "peak_categories": {"code": 6350192, "tensors": 501223424, "constants": 2850833, "scratchpad": 67108864, "misc": 8545088, "dma_rings": 2507520}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 481544320, "allocator_peak_reserved_bytes": 501219328, "total_seconds": 20.18780482839793} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/140.log b/validation/sentence-transformers/2026-11-03-top100/logs/140.log new file mode 100644 index 0000000000000000000000000000000000000000..5da0c4f4975269d9a067855c991b52b450a445de --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/140.log @@ -0,0 +1,64 @@ +/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/configuration_utils.py:723: FutureWarning: `rope_scaling` is deprecated and will be removed in a future version. Set `rope_parameters` instead, with `rope_type` and `rope_theta` included. + warnings.warn( +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/140/run.py", line 63, in + stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1) + ~~~~~^^ + File "/tmp/neuron-top100-sweep/runs/140/run.py", line 58, in score + q=model.encode_query([query],batch_size=4,show_progress_bar=False,**kw) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 370, in encode_query + return self.encode( + ~~~~~~~~~~~^ + inputs=inputs, + ^^^^^^^^^^^^^^ + ...<14 lines>... + **kwargs, + ^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py", line 124, in decorate_context + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 895, in encode + all_embeddings = self._inference(inputs, device=device, **inference_kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py", line 124, in decorate_context + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 963, in _inference + out_features = self(features, **kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 600, in forward + input = module(input, **module_kwargs) + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 1647, in forward + model_output = model_method(**filtered_kwargs) + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py", line 901, in forward + (embedding_output, attention_mask, rope_embeds, length) = self.embeddings( + ~~~~~~~~~~~~~~~^ + unpad_inputs, + ^^^^^^^^^^^^^ + ...<5 lines>... + inputs_embeds=inputs_embeds + ^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl + return self._call_impl(*args, **kwargs) + ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl + return forward_call(*args, **kwargs) + File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py", line 392, in forward + rope_cos = rope_cos[position_ids].unsqueeze(2) # [bs, seq_len, 1, dim] + ~~~~~~~~^^^^^^^^^^^^^^ +IndexError: index 140471200382993 is out of bounds for dimension 0 with size 11 +{"index": 140, "model": "Alibaba-NLP/gte-base-en-v1.5", "revision": "a829fd0e060bb84554da0dfd354d0de0f7712b7f", "trending_rank": null, "downloads_rank": 71, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": true, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:55:35.076933+00:00", "physical_visible_core": "12", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 1.5855842670425773, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "status": "error", "stage": "cpu_inference", "error_type": "IndexError", "error": "index 140471200382993 is out of bounds for dimension 0 with size 11", "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/140/run.py\", line 63, in \n stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/140/run.py\", line 58, in score\n q=model.encode_query([query],batch_size=4,show_progress_bar=False,**kw)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 370, in encode_query\n return self.encode(\n ~~~~~~~~~~~^\n inputs=inputs,\n ^^^^^^^^^^^^^^\n ...<14 lines>...\n **kwargs,\n ^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 895, in encode\n all_embeddings = self._inference(inputs, device=device, **inference_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 963, in _inference\n out_features = self(features, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 600, in forward\n input = module(input, **module_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 1647, in forward\n model_output = model_method(**filtered_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 901, in forward\n (embedding_output, attention_mask, rope_embeds, length) = self.embeddings(\n ~~~~~~~~~~~~~~~^\n unpad_inputs,\n ^^^^^^^^^^^^^\n ...<5 lines>...\n inputs_embeds=inputs_embeds\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 392, in forward\n rope_cos = rope_cos[position_ids].unsqueeze(2) # [bs, seq_len, 1, dim]\n ~~~~~~~~^^^^^^^^^^^^^^\nIndexError: index 140471200382993 is out of bounds for dimension 0 with size 11\n", "result": "FAIL(forward)", "total_seconds": 12.225869985297322} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/144.log b/validation/sentence-transformers/2026-11-03-top100/logs/144.log new file mode 100644 index 0000000000000000000000000000000000000000..84e847524620ac9cbac218a12c7325ae745b966a --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/144.log @@ -0,0 +1,5 @@ +CPU [0.4463503956794739, 0.692706823348999, 0.6985108852386475, 0.6134428977966309] +2026-Nov-03 15:56:23.036324 2721788:2721788 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +{"index": 144, "model": "minishlab/potion-base-8M", "revision": "bf8b056651a2c21b8d2565580b8569da283cab23", "trending_rank": null, "downloads_rank": 75, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:56:13.809543+00:00", "physical_visible_core": "8", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 0.3890756834298372, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "embedding_devices": ["neuron:0", "neuron:0"], "cpu_scores": [0.4463503956794739, 0.692706823348999, 0.6985108852386475, 0.6134428977966309], "cpu_seconds": 0.06325524486601353, "cpu_top_document": 3, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 6.991000535897911, "neuron_scores": [0.4463503956794739, 0.6927067637443542, 0.6985103487968445, 0.6134430170059204], "max_abs_error": 5.364418029785156e-07, "neuron_top_document": 3, "mars_first": false, "cpu_parity": true, "neuron_repeat_seconds": 0.007872754707932472, "repeat_max_abs_error": 0.0, "repeat_stable": true, "status": "executed", "result": "FAIL(output)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 72, "sample_interval_seconds": 0.1, "peak_bytes": 40488680, "peak_categories": {"code": 4221032, "tensors": 33558528, "constants": 327680, "misc": 2111104, "dma_rings": 270336}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 30251264, "allocator_peak_reserved_bytes": 33554432, "total_seconds": 25.33328312728554} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/146.log b/validation/sentence-transformers/2026-11-03-top100/logs/146.log new file mode 100644 index 0000000000000000000000000000000000000000..314ce88404cba7271d4bb73fc4f009c6b69eed71 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/146.log @@ -0,0 +1,5 @@ +CPU [0.46113887429237366, 0.7457321882247925, 0.8234667181968689, 0.7024552822113037] +2026-Nov-03 15:56:47.229090 2726999:2726999 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +{"index": 146, "model": "TimKond/S-PubMedBert-MedQuAD", "revision": "b73d84decb1da6bd4c1cf084a1b6c6602157d267", "trending_rank": null, "downloads_rank": 77, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:56:33.415911+00:00", "physical_visible_core": "4", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 1.2769848257303238, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "embedding_devices": ["neuron:0", "neuron:0"], "cpu_scores": [0.46113887429237366, 0.7457321882247925, 0.8234667181968689, 0.7024552822113037], "cpu_seconds": 0.15781457629054785, "cpu_top_document": 3, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 0.31044141575694084, "neuron_scores": [0.46113866567611694, 0.745732307434082, 0.823466420173645, 0.7024555206298828], "max_abs_error": 2.980232238769531e-07, "neuron_top_document": 3, "mars_first": false, "cpu_parity": true, "neuron_repeat_seconds": 0.03502273000776768, "repeat_max_abs_error": 0.0, "repeat_stable": true, "status": "executed", "result": "FAIL(output)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 6, "sample_interval_seconds": 0.1, "peak_bytes": 589734025, "peak_categories": {"code": 6608056, "tensors": 501223424, "constants": 3309585, "scratchpad": 67108864, "misc": 9499584, "dma_rings": 1984512}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 482003968, "allocator_peak_reserved_bytes": 501219328, "total_seconds": 21.299358570948243} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/158.log b/validation/sentence-transformers/2026-11-03-top100/logs/158.log new file mode 100644 index 0000000000000000000000000000000000000000..3597c525d0ac42de027a8a9182c0fbda148ddb2d --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/158.log @@ -0,0 +1,76 @@ +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/158/run.py", line 50, in + model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']}) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 46, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 193, in __init__ + super().__init__( + ~~~~~~~~~~~~~~~~^ + model_name_or_path=model_name_or_path, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ...<13 lines>... + default_prompt_name=default_prompt_name, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 256, in __init__ + modules, self.module_kwargs = self._load_modules( + ~~~~~~~~~~~~~~~~~~^ + model_name_or_path, + ^^^^^^^^^^^^^^^^^^^ + ...<7 lines>... + config_kwargs=config_kwargs, + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 1211, in _load_modules + return self._load_config_modules(model_name_or_path, **load_kwargs) + ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 1431, in _load_config_modules + module = module_class.load( + model_name_or_path, + ...<12 lines>... + **extra_load_kwargs, + ) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 2641, in load + return cls(model_name_or_path=model_name_or_path, **init_kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py", line 92, in wrapper + return func(*args, **kwargs) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 855, in __init__ + self.model = self._load_model( + ~~~~~~~~~~~~~~~~^ + model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py", line 2343, in _load_model + return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs) + ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py", line 389, in from_pretrained + return model_class.from_pretrained( + ~~~~~~~~~~~~~~~~~~~~~~~~~~~^ + pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py", line 4356, in from_pretrained + loading_info = cls._finalize_model_loading(model, load_config, loading_info) + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py", line 4524, in _finalize_model_loading + model._move_missing_keys_from_meta_to_device( + ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ + loading_info.missing_and_mismatched(), + ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + ...<2 lines>... + load_config.hf_quantizer, + ^^^^^^^^^^^^^^^^^^^^^^^^^ + ) + ^ + File "/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py", line 4781, in _move_missing_keys_from_meta_to_device + for key in missing_keys - self.all_tied_weights_keys.keys(): + ^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py", line 1972, in __getattr__ + raise AttributeError( + f"'{type(self).__name__}' object has no attribute '{name}'" + ) +AttributeError: 'NVEmbedModel' object has no attribute 'all_tied_weights_keys'. Did you mean: '_tied_weights_keys'? +{"index": 158, "model": "nvidia/NV-Embed-v2", "revision": "3fa59658547db50a1e8e3346cf057fd0c77ed6ef", "trending_rank": null, "downloads_rank": 93, "class": "SentenceTransformer", "dtype": "bfloat16", "attention": "eager", "trust_remote_code": true, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:58:12.973659+00:00", "physical_visible_core": "0", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "status": "error", "stage": "load_cpu", "error_type": "AttributeError", "error": "'NVEmbedModel' object has no attribute 'all_tied_weights_keys'", "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/158/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 855, in __init__\n self.model = self._load_model(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2343, in _load_model\n return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 389, in from_pretrained\n return model_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4356, in from_pretrained\n loading_info = cls._finalize_model_loading(model, load_config, loading_info)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4524, in _finalize_model_loading\n model._move_missing_keys_from_meta_to_device(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n loading_info.missing_and_mismatched(),\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<2 lines>...\n load_config.hf_quantizer,\n ^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4781, in _move_missing_keys_from_meta_to_device\n for key in missing_keys - self.all_tied_weights_keys.keys():\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1972, in __getattr__\n raise AttributeError(\n f\"'{type(self).__name__}' object has no attribute '{name}'\"\n )\nAttributeError: 'NVEmbedModel' object has no attribute 'all_tied_weights_keys'. Did you mean: '_tied_weights_keys'?\n", "result": "FAIL(load)", "total_seconds": 29.60385298728943} diff --git a/validation/sentence-transformers/2026-11-03-top100/logs/164.log b/validation/sentence-transformers/2026-11-03-top100/logs/164.log new file mode 100644 index 0000000000000000000000000000000000000000..592b03a04223233c6e5f07b5092ee98efbc9b1cd --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/logs/164.log @@ -0,0 +1,18 @@ +CPU [37.162418365478516, 43.29322814941406, 43.17018127441406, 42.00007629394531] +2026-Nov-03 16:00:02.462563 2793780:2793780 WARN NRT:nrt_init dma-buf is not supported due to incompatible Libfabric. Falling back to p2p for efa memory registration. (this log repeats as INFO level) +/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch_neuronx/nki_kernel.py:85: UserWarning: NKI_ENABLE_TRACE_CACHE=1: the NKI kernel compile cache is persisted across processes. The caching process may not capture all kernel environment dependencies or non-argument values and can yield stale cache hits; see the torch-neuronx environment variables documentation for details. Set NKI_ENABLE_TRACE_CACHE=0 to disable. + _warn_trace_cache_once() +Traceback (most recent call last): + File "/tmp/neuron-top100-sweep/runs/164/run.py", line 69, in + stage='neuron_inference';t=time.monotonic();actual=score();r['score_device']=str(actual.device) + ~~~~~^^ + File "/tmp/neuron-top100-sweep/runs/164/run.py", line 61, in score + values=model.similarity(q,d) + File "/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py", line 1072, in similarity + return self._similarity(embeddings1, embeddings2) + ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^ + File "/home/jingyahuang/sentence-transformers/sentence_transformers/util/similarity.py", line 115, in dot_score + return torch.mm(a, b.transpose(0, 1)).to_dense() + ~~~~~~~~~~~^^^^^^ +RuntimeError: Inference tensors do not track version counter. +{"index": 164, "model": "sentence-transformers/multi-qa-MiniLM-L6-dot-v1", "revision": "4151c507ffb0f2fcd311cf431f54b5fc7d097851", "trending_rank": null, "downloads_rank": 100, "class": "SentenceTransformer", "dtype": "float32", "attention": "sdpa", "trust_remote_code": false, "config_kwargs": {}, "excluded": null, "exclusion": null, "started_at": "2026-11-03T15:59:45.659267+00:00", "physical_visible_core": "0", "torch": "2.14.0+cpu", "transformers": "5.22.1", "sentence_transformers": "6.3.0.dev0", "python": "3.14.4", "query": "Which planet is known as the Red Planet?", "documents": ["Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet."], "batch_size": 4, "load_seconds": 1.0640968950465322, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "embedding_devices": ["neuron:0", "neuron:0"], "cpu_scores": [37.162418365478516, 43.29322814941406, 43.17018127441406, 42.00007629394531], "cpu_seconds": 0.06058734655380249, "cpu_top_document": 2, "model_device": "neuron:0", "status": "error", "stage": "neuron_inference", "error_type": "RuntimeError", "error": "Inference tensors do not track version counter.", "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/164/run.py\", line 69, in \n stage='neuron_inference';t=time.monotonic();actual=score();r['score_device']=str(actual.device)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/164/run.py\", line 61, in score\n values=model.similarity(q,d)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 1072, in similarity\n return self._similarity(embeddings1, embeddings2)\n ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/similarity.py\", line 115, in dot_score\n return torch.mm(a, b.transpose(0, 1)).to_dense()\n ~~~~~~~~~~~^^^^^^\nRuntimeError: Inference tensors do not track version counter.\n", "result": "FAIL(forward)", "memory_monitor": {"method": "Neuron runtime HBM usage breakdown sampled every 100 ms", "sample_count": 5, "sample_interval_seconds": 0.1, "peak_bytes": 223731977, "peak_categories": {"code": 6030712, "tensors": 136318976, "constants": 2785297, "scratchpad": 67108864, "misc": 8847488, "dma_rings": 2640640}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 97223168, "allocator_peak_reserved_bytes": 136314880, "total_seconds": 24.259669181890786} diff --git a/validation/sentence-transformers/2026-11-03-top100/manifest.json b/validation/sentence-transformers/2026-11-03-top100/manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..2658893d10dc3b5dc8de796b1305c53e3471cfa6 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/manifest.json @@ -0,0 +1,2310 @@ +[ + { + "index": 1, + "model": "google/embeddinggemma-2", + "revision": "f9972ac22e696a105c482202646979e33e4b5a1e", + "trending_rank": 1, + "downloads_rank": 79, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": { + "vision_config": null, + "audio_config": null + }, + "excluded": null, + "exclusion": null + }, + { + "index": 2, + "model": "sentence-transformers/all-MiniLM-L6-v2", + "revision": "1110a243fdf4706b3f48f1d95db1a4f5529b4d41", + "trending_rank": 2, + "downloads_rank": 1, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null + }, + { + "index": 3, + "model": "BAAI/bge-m3", + "revision": "5617a9f61b028005a4858fdac845db406aefb181", + "trending_rank": 3, + "downloads_rank": 4, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null 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"categories": {"code": 3842944, "tensors": 2097152, "misc": 1144320, "dma_rings": 57344}}, {"elapsed_seconds": 0.10029691457748413, "bytes": 142073100, "categories": {"code": 4216072, "tensors": 134217728, "constants": 655364, "misc": 2607104, "dma_rings": 376832}}, {"elapsed_seconds": 0.2003889186307788, "bytes": 214733676, "categories": {"code": 5109856, "tensors": 134217728, "constants": 1572876, "scratchpad": 67108864, "misc": 5310720, "dma_rings": 1413632}}, {"elapsed_seconds": 0.300482427701354, "bytes": 221070273, "categories": {"code": 5699824, "tensors": 136318976, "constants": 2261009, "scratchpad": 67108864, "misc": 7583680, "dma_rings": 2097920}}, {"elapsed_seconds": 0.346355440095067, "bytes": 223731977, "categories": {"code": 6030712, "tensors": 136318976, "constants": 2785297, "scratchpad": 67108864, "misc": 8847488, "dma_rings": 2640640}}] \ No newline at end of file diff --git a/validation/sentence-transformers/2026-11-03-top100/results.csv b/validation/sentence-transformers/2026-11-03-top100/results.csv new file mode 100644 index 0000000000000000000000000000000000000000..ba9f2574183b4ced471f11c97af96fcf07aa58e8 --- /dev/null +++ b/validation/sentence-transformers/2026-11-03-top100/results.csv @@ -0,0 +1,165 @@ +model,trending_rank,downloads_rank,class,dtype,attention,result,stage,cpu_top_document,neuron_top_document,mars_first,cpu_parity,max_abs_error,hbm_peak_gb,hbm_capacity_gb,revision +google/embeddinggemma-2,1,79,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.3709068298339844e-06,1.2238852018490434,24.0,f9972ac22e696a105c482202646979e33e4b5a1e +sentence-transformers/all-MiniLM-L6-v2,2,1,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,7.748603820800781e-07,0.20904067251831293,24.0,1110a243fdf4706b3f48f1d95db1a4f5529b4d41 +BAAI/bge-m3,3,4,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,5.960464477539062e-07,2.2685502702370286,24.0,5617a9f61b028005a4858fdac845db406aefb181 +kakaocorp/kanana-2-3b-embedding,4,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.2516975402832031e-06,12.084395893849432,24.0,2c85dbe61af8ff033d2c9d46a686c665153069aa +google/embeddinggemma-300m,5,37,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,5.066394805908203e-07,1.3346415031701326,24.0,57c266a740f537b4dc058e1b0cda161fd15afa75 +nvidia/Nemotron-3.5-Embed-1B-BF16,6,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,5.364418029785156e-07,5.927469746209681,24.0,e24ca1e346bcc53572bd7bdc02b3e8ebf66c197c +nvidia/Nemotron-3.5-Rerank-8B-BF16,7,,CrossEncoder,bfloat16,sdpa,FAIL(output),,2,2,True,False,0.008536696434020996,15.77404351066798,24.0,f88f8d9104726747791283ab156d2fcdb29e90a7 +BAAI/bge-reranker-v2-m3,8,7,CrossEncoder,float32,sdpa,PASS,,2,2,True,True,7.748603820800781e-07,2.226724443025887,24.0,953dc6f6f85a1b2dbfca4c34a2796e7dde08d41e +Qwen/Qwen3-Embedding-0.6B,9,12,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,5.364418029785156e-07,2.3782112384214997,24.0,97b0c614be4d77ee51c0cef4e5f07c00f9eb65b3 +Qwen/Qwen3-VL-Embedding-2B,10,67,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.0132789611816406e-06,8.099787437357008,24.0,9f2f7e710d6d81056aa5c0a4f04764fec6bb7bda +kakaocorp/kanana-2-1.3b-embedding,11,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.3709068298339844e-06,5.0805351147428155,24.0,107b09b19ea3628acbd42615ee9ad59b82f604a3 +intfloat/multilingual-e5-small,12,9,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.1920928955078125e-07,0.5393597865477204,24.0,614241f622f53c4eeff9890bdc4f31cfecc418b3 +Qwen/Qwen3-Reranker-0.6B,13,40,CrossEncoder,float32,sdpa,PASS,,2,2,True,True,1.33514404296875e-05,3.670168516226113,24.0,e61197ed45024b0ed8a2d74b80b4d909f1255473 +Qwen/Qwen3-Embedding-8B,14,26,SentenceTransformer,bfloat16,sdpa,PASS,,2,2,True,True,0.000370025634765625,14.27409886289388,24.0,1d8ad4ca9b3dd8059ad90a75d4983776a23d44af +perplexity-ai/pplx-embed-v2-late-0.6b,15,,MultiVectorEncoder,float32,sdpa,PASS,,2,2,True,True,1.9073486328125e-06,2.457300760783255,24.0,7bba8e7cf2075dec747fa8557f41eb90e70361ed +hotchpotch/bekko-static-embedding-v1,16,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,2.384185791015625e-07,0.3920571357011795,24.0,c18167b8f244c1bc6de21ce9b710bac8a29c4615 +cross-encoder/ms-marco-MiniLM-L6-v2,17,2,CrossEncoder,float32,sdpa,PASS,,2,2,True,True,3.814697265625e-06,0.20346579421311617,24.0,233902d25c440f23af6f7d6e94d2946bac0bee0a +intfloat/multilingual-e5-base,18,16,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,8.940696716308594e-07,1.1819792250171304,24.0,d128750597153bb5987e10b1c3493a34e5a4502a +BAAI/bge-small-en-v1.5,19,3,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.3113021850585938e-06,0.22558351699262857,24.0,5c38ec7c405ec4b44b94cc5a9bb96e735b38267a +naver/splade-v3,20,,SentenceTransformer,float32,sdpa,EXCLUDED,,,,,,,,,fdfeceb91d7b9de7985b38addd3ba9f53a59a355 +Omartificial-Intelligence-Space/Arabic-Triplet-Matryoshka-V2,21,,SentenceTransformer,float32,sdpa,FAIL(output),,4,4,False,True,2.682209014892578e-07,0.6478953966870904,24.0,17b87422aa4bfb3b478369299e701070b308314f +Qwen/Qwen3-Reranker-4B,22,22,CrossEncoder,float32,sdpa,PASS,,2,2,True,True,9.5367431640625e-06,18.65531821269542,24.0,22e683669bc0f0bd69640a1354a6d0aebcfeede5 +litert-community/embeddinggemma-300m,23,,SentenceTransformer,float32,sdpa,FAIL(load),load_cpu,,,,,,,,459f1d37fec9635eb1730ebdbc219bfc3226c8e7 +Qwen/Qwen3-VL-Embedding-8B,24,54,SentenceTransformer,bfloat16,sdpa,FAIL(output),,2,2,True,False,0.002091825008392334,15.394332815892994,24.0,2c4565515e0f265c6511776e7193b22c0968ddc7 +Octen/Octen-Embedding-0.6B,25,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.0728836059570312e-06,2.3792887115851045,24.0,b54faa2ba2ae9eb618f88526cec6dae3287eb5f8 +ibm-granite/granite-embedding-311m-multilingual-r2,26,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,8.344650268554688e-07,1.2832580963149667,24.0,44399559930365213510b1ee2eb15ded83374f0e +unsloth/embeddinggemma-2,27,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.3709068298339844e-06,1.2258383268490434,24.0,c8f89cc7ecb4ba5122cd15fdd487422b2b487daf +nvidia/Nemotron-3.5-Embed-8B-BF16,28,,SentenceTransformer,bfloat16,sdpa,PASS,,2,2,True,True,0.0005546212196350098,15.798520457930863,24.0,781e779ee4ca9c2d2a4f38321993556baeab49a1 +BrunoHays/embeddinggemma-2-nullspace-audio,29,,SentenceTransformer,float32,sdpa,FAIL(load),load_cpu,,,,,,,,4e54c6816e4ba368be62885788974458f2748adf +sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2,30,5,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.7881393432617188e-07,0.5393597865477204,24.0,e8f8c211226b894fcb81acc59f3b34ba3efd5f42 +BAAI/bge-reranker-v2-gemma,31,,CrossEncoder,float32,sdpa,FAIL(output),,3,3,False,True,5.960464477539063e-08,9.509233427233994,24.0,1787044f8b6fb740a9de4557c3a12377f84d9e17 +Snowflake/snowflake-arctic-embed-m,32,87,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,3.5762786865234375e-07,0.5483529502525926,24.0,fc74610d18462d218e312aa986ec5c8a75a98152 +Snowflake/snowflake-arctic-embed-m-v2.0,33,,SentenceTransformer,float32,sdpa,FAIL(forward),cpu_inference,,,,,,,,95c2741480856aa9666782eb4afe11959938017f +Qwen/Qwen3-Reranker-8B,34,,CrossEncoder,bfloat16,sdpa,FAIL(output),,2,2,True,False,0.0625,17.86173569690436,24.0,77d193c791ed757ca307ee72715aa132723da912 +Qwen/Qwen3-Embedding-4B,35,24,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,4.76837158203125e-07,15.347929389216006,24.0,5cf2132abc99cad020ac570b19d031efec650f2b +nvidia/llama-nemotron-rerank-vl-1b-v2,36,,CrossEncoder,float32,sdpa,PASS,,2,2,True,True,3.814697265625e-06,6.565492783673108,24.0,b8a9987b05b75db5ad949c825cbcbf6eb7c48b5a +Octen/Octen-Embedding-8B,37,,SentenceTransformer,bfloat16,sdpa,PASS,,2,2,True,True,0.001355588436126709,14.273378145880997,24.0,88695e4f8ed87b4ce08df2fea6ff25bfe0f9875b +Octen/Octen-Embedding-4B,38,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.0132789611816406e-06,15.349551239050925,24.0,dcfdcdaf02e2f4fc26a22ee36936b2afcad8b208 +Octen/Octen-Embedding-8B-INT8,39,,SentenceTransformer,bfloat16,sdpa,EXCLUDED,,,,,,,,,2220d20a1720017df6a352884c0c3099aed8de15 +jinaai/jina-embeddings-v5-text-small,40,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,0.0006766319274902344,1.590733622200787,24.0,dd76d535f5447ca3897a9c893fb1e612ead98192 +microsoft/harrier-oss-v1-270m,41,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,6.556510925292969e-07,1.129159995354712,24.0,31de22b673913c7d658c0f03f792d77c2dcf8ebd +jinaai/jina-embeddings-v5-omni-small,42,48,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,0.0006766319274902344,5.2039363430812955,24.0,950200abde3a3bcf3d5bdfe5d28fb5bb5e7dfbb0 +Octen/Octen-Embedding-4B-INT8,43,,SentenceTransformer,float32,sdpa,EXCLUDED,,,,,,,,,7397789b62a36db1304f341ed04468d9f4d10a14 +hotchpotch/bekko-embedding-v1-a8m,44,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,3.5762786865234375e-07,0.5253349477425218,24.0,c721113d59a1d91b447450324f51c4b3332c924a +KaLM-Embedding/KaLM-Reranker-V1-Nano-R2,45,,CrossEncoder,float32,sdpa,PASS,,2,2,True,True,1.6689300537109375e-06,3.8357916260138154,24.0,48a5b221014ebb91f10400ffc7ef31f4960143ed +tencent/WeMM-Embedding-2B,46,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,7.152557373046875e-07,10.346037835814059,24.0,bbd6cd4bf52cfc6716f752a2df80b2706720bd95 +tencent/WeMM-Embedding-9B,47,,SentenceTransformer,bfloat16,sdpa,PASS,,2,2,True,True,0.0012020766735076904,17.913388256914914,24.0,00c52839de57a6d4fd5b78cf5522ccf0ac8ea482 +Dibachain/Diba-Embed,48,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,5.364418029785156e-07,2.3782112384214997,24.0,9fe78de42f427081cce4a389177f9c1fea326dcf +kyr0/Winzling-Embed-a8m-64k,49,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,3.5762786865234375e-07,0.2507902989163995,24.0,bfa8af8a8fbf3beb12a93a14d6f5b51875a36214 +Linkup-Platform/linkup-sparseup-embed-v1,50,,SentenceTransformer,float32,sdpa,EXCLUDED,,,,,,,,,08314498d4f6a3a205b930ab9f27001404ea94b8 +RiverRider/motherlode-code-small-en-v0.1,51,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.1324882507324219e-06,0.22558351699262857,24.0,10c3db34a27980cbca72227f736807aa8be487bb +junaid008/hindko-embeddings,52,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,7.152557373046875e-07,2.2043784195557237,24.0,432690c2f36c31dfa9da8b58bfe763272f7614cb +lightonai/SlideOn,53,,SentenceTransformer,float32,sdpa,EXCLUDED,,,,,,,,,370c600e9886afc43ff8026695261e56ecfaa011 +HukukcuApp/tr-legal-embedding-gemma-2,54,,SentenceTransformer,float32,sdpa,FAIL(load),load_cpu,,,,,,,,a33e497f3f123019d3b03fe40082992fffeac728 +abacusai/Smaug-AI-Image-Detector,55,,SentenceTransformer,float32,sdpa,EXCLUDED,,,,,,,,,c7c95951e04a87b884a4ad479401b1128c3903bd +papr-ai/papr-embed-code-1-4b,56,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,6.556510925292969e-07,15.344023139216006,24.0,2abaf9b8b8dbcda87259cbd274c75c40f085d8c7 +tomaarsen/embeddinggemma-2-512d,57,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.430511474609375e-06,1.1596503490582108,24.0,f7e16920485c2666d65ec566debc023e5e9d0319 +cointegrated/rubert-tiny2,58,85,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.1920928955078125e-06,0.2534896144643426,24.0,e8ed3b0c8bbf4fb6984c3de043bf7d2f4e5969ae +cross-encoder/ms-marco-MiniLM-L4-v2,59,18,CrossEncoder,float32,sdpa,PASS,,2,2,True,True,4.76837158203125e-06,0.19760641921311617,24.0,777b2f369bc1c2f850df8bd367ed1654bda4497b +sentence-transformers/LaBSE,60,56,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.1324882507324219e-06,1.8975434163585305,24.0,836121a0533e5664b21c7aacc5d22951f2b8b25b +sentence-transformers/all-MiniLM-L12-v2,61,23,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,2.682209014892578e-07,0.22466376516968012,24.0,a50ef00143b4d5391434df20ae11632588ac25be +sentence-transformers/all-mpnet-base-v2,62,6,SentenceTransformer,float32,eager,PASS,,2,2,True,True,1.0728836059570312e-06,0.5646491246297956,24.0,e8c3b32edf5434bc2275fc9bab85f82640a19130 +sentence-transformers/clip-ViT-B-32-multilingual-v1,63,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,4.76837158203125e-07,0.6163174295797944,24.0,58edf8cada9e398793dca955574a48cbb7f18be2 +sentence-transformers/clip-ViT-B-32,64,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,2.980232238769531e-07,0.7480063820257783,24.0,327ab6726d33c0e22f920c83f2ff9e4bd38ca37f +sentence-transformers/msmarco-MiniLM-L6-v3,65,97,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,5.960464477539062e-07,0.20904544088989496,24.0,fea93b3df3924e5649a4e322c345f951239d2c13 +cross-encoder/mmarco-mMiniLMv2-L12-H384-v1,66,39,CrossEncoder,float32,sdpa,PASS,,2,2,True,True,7.152557373046875e-06,0.5348287047818303,24.0,1427fd652930e4ba29e8149678df786c240d8825 +moka-ai/m3e-base,67,,SentenceTransformer,float32,sdpa,FAIL(output),,3,3,False,True,3.5762786865234375e-07,0.5224026003852487,24.0,764b537a0e50e5c7d64db883f2d2e051cbe3c64c +BAAI/bge-reranker-base,68,21,CrossEncoder,float32,sdpa,PASS,,2,2,True,True,4.172325134277344e-07,1.1738110156729817,24.0,2cfc18c9415c912f9d8155881c133215df768a70 +BAAI/bge-base-en-v1.5,69,13,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.2516975402832031e-06,0.550099560059607,24.0,a5beb1e3e68b9ab74eb54cfd186867f64f240e1a +jinaai/jina-embeddings-v2-base-en,70,88,SentenceTransformer,float32,sdpa,FAIL(load),load_cpu,,,,,,,,322d4d7e2f35e84137961a65af894fda0385eb7a +nomic-ai/nomic-embed-text-v1.5,71,8,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,2.980232238769531e-07,0.6785909170284867,24.0,e9b6763023c676ca8431644204f50c2b100d9aab +nasa-impact/nasa-smd-ibm-st-v2,72,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.0728836059570312e-06,0.6115323463454843,24.0,e4a3e22048f0173ef150470cfbf67e9e8aaf4f8c +Alibaba-NLP/gte-large-en-v1.5,73,27,SentenceTransformer,float32,sdpa,FAIL(forward),cpu_inference,,,,,,,,104333d6af6f97649377c2afbde10a7704870c7b +udrearobert999/multi-qa-mpnet-base-cos-v1-contrastive-2e-1000samples,74,,SentenceTransformer,float32,eager,PASS,,2,2,True,True,1.1324882507324219e-06,0.5626998143270612,24.0,8a12b2b5886621830108824ffbb1382e66803888 +nvidia/NV-Embed-v1,75,,SentenceTransformer,bfloat16,sdpa,FAIL(load),load_cpu,,,,,,,,2e8b322e2b738a383dae0dde5fa19e0b28a5bb11 +deepvk/USER-base,76,,SentenceTransformer,float32,eager,PASS,,2,2,True,True,1.2516975402832031e-06,0.6232241913676262,24.0,e8446472f6024df155a04b2f0911b6044cabc51f +Jaume/gemma-2b-embeddings,77,,SentenceTransformer,float32,sdpa,FAIL(output),,3,3,False,True,6.556510925292969e-07,9.508606069721282,24.0,86431f65d7c3f66b2af096c61e614a2958f191f1 +Alibaba-NLP/gte-multilingual-reranker-base,78,,CrossEncoder,float32,sdpa,FAIL(forward),cpu_inference,,,,,,,,8215cf04918ba6f7b6a62bb44238ce2953d8831c +akhooli/Arabic-SBERT-100K,79,,SentenceTransformer,float32,sdpa,FAIL(output),,4,4,False,True,2.682209014892578e-07,0.6478953966870904,24.0,67199ee95d81bb10047c946b1b4268c8703b83db +jinaai/jina-colbert-v2,80,,MultiVectorEncoder,float32,eager,PASS,,2,2,True,True,1.1444091796875e-05,2.2476080134510994,24.0,a9dc5cd7293d4c71dbbba04829923ba4d0e4f6ea +jinaai/jina-embeddings-v3,81,32,SentenceTransformer,float32,eager,FAIL(load),load_cpu,,,,,,,,ab036b023d30b4d1138c4c3bfa9f0c445ab455d6 +dragonkue/bge-reranker-v2-m3-ko,82,,CrossEncoder,float32,sdpa,PASS,,2,2,True,True,1.7881393432617188e-07,2.226724443025887,24.0,2aca5884ecac490192af9ebd86836d9073d826cd +meandyou200175/phobert-finetune,83,,SentenceTransformer,float32,sdpa,FAIL(output),,4,4,False,True,4.172325134277344e-07,0.653023392893374,24.0,26e5f91ad1eb94b0af813021a2b7097ae4ba228e +Snowflake/snowflake-arctic-embed-l-v2.0,84,19,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,4.172325134277344e-07,2.2685545096173882,24.0,ac6544c8a46e00af67e330e85a9028c66b8cfd9a +perticarari/fine-tuned-sts-embedder,85,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,5.960464477539062e-07,0.20903876516968012,24.0,ca5311f5764c05eb3dae4f5fb54056e614f90f00 +ai-forever/FRIDA,86,62,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,8.344650268554688e-07,3.3286698097363114,24.0,850455b605544a944739b25f81ddf812b6e3d0d5 +Alibaba-NLP/gte-modernbert-base,87,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,2.384185791015625e-07,0.6767938891425729,24.0,e7f32e3c00f91d699e8c43b53106206bcc72bb22 +Alibaba-NLP/gte-reranker-modernbert-base,88,36,CrossEncoder,float32,sdpa,PASS,,2,2,True,True,1.7881393432617188e-07,0.6695965128019452,24.0,f7481e6055501a30fb19d090657df9ec1f79ab2c +vidore/colqwen2.5-v0.2,89,,MultiVectorEncoder,float32,sdpa,FAIL(output),,4,4,False,True,5.7220458984375e-06,14.48814355675131,24.0,dcbe8d9cede518bce830488364ba0e40c873645b +ibm-granite/granite-embedding-30m-sparse,90,,SentenceTransformer,float32,sdpa,EXCLUDED,,,,,,,,,ad82b1fd09541c998c8d45045d601c51fdb8a9b7 +deepvk/USER2-small,91,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.7881393432617188e-07,0.2447022134438157,24.0,23f65b34cf7632032061f5cc66c14714e6d4cee4 +mixedbread-ai/mxbai-rerank-base-v2,92,,CrossEncoder,float32,sdpa,PASS,,2,2,True,True,1.1920928955078125e-07,2.065345217473805,24.0,3ea9d4dffa7d12a4f366be8e275c349de9fc9865 +sabafallah/bge-reranker-v2-m3-Q4_K_M-GGUF,93,,CrossEncoder,float32,sdpa,EXCLUDED,,,,,,,,,d1fb0d915c94bd34276a270691604ec24caa521f +nathankim/fine_tuned_resume_matcher,94,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.3113021850585938e-06,0.20905593130737543,24.0,2f9863e8ed5ee249b3291ba4818e0a8dda261c31 +mradermacher/Qwen3-Reranker-0.6B-GGUF,95,,SentenceTransformer,float32,sdpa,EXCLUDED,,,,,,,,,6727da811d2cc45b078b744bffaaab122a0691da +sdadas/polish-reranker-roberta-v3,96,,CrossEncoder,float32,sdpa,PASS,,2,2,True,True,5.960464477539063e-08,1.804555562324822,24.0,8943df3d4ffa6b829bd80acf3a9aca17c553da4e +VAGOsolutions/SauerkrautLM-Reason-Multi-ColBERT-15m,97,,MultiVectorEncoder,float32,sdpa,PASS,,2,2,True,True,1.9073486328125e-06,0.20930115226656199,24.0,fcf980ab2fc3f6f22f2b0ad1ccc80d3c210e28a5 +ibm-granite/granite-embedding-english-r2,98,,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.1920928955078125e-07,0.6767862597480416,24.0,47ea694b257b703fee9253d75c2b1f2985180498 +ibm-granite/granite-embedding-small-english-r2,99,15,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.3709068298339844e-06,0.29724300000816584,24.0,2ab6fa8ea2d674564defd37171ae19079b864b33 +mlx-community/embeddinggemma-300m-bf16,100,,SentenceTransformer,float32,sdpa,EXCLUDED,,,,,,,,,2f420efb007317a1ef2aa1608f87ef24226e6807 +BAAI/bge-large-en-v1.5,,10,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,3.5762786865234375e-07,1.3613299885764718,24.0,d4aa6901d3a41ba39fb536a557fa166f842b0e09 +sentence-transformers/paraphrase-multilingual-mpnet-base-v2,,11,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.1920928955078125e-07,1.1819792250171304,24.0,4328cf26390c98c5e3c738b4460a05b95f4911f5 +intfloat/multilingual-e5-large,,14,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.4901161193847656e-06,2.204374604858458,24.0,3d7cfbdacd47fdda877c5cd8a79fbcc4f2a574f3 +datasocietyco/bge-base-en-v1.5-course-recommender-v5,,17,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.1324882507324219e-06,0.550099560059607,24.0,2b069eed51ce7bc2beeaa7e3eea1a01c48ef3d29 +sentence-transformers/all-distilroberta-v1,,20,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.3113021850585938e-06,0.4220791617408395,24.0,842eaed40bee4d61673a81c92d5689a8fed7a09f +mixedbread-ai/mxbai-embed-large-v1,,25,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,4.172325134277344e-07,1.3613488981500268,24.0,b33106f585b9ce46904ad7443a3b52b7a63e231c +intfloat/multilingual-e5-large-instruct,,28,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.3709068298339844e-06,2.204374604858458,24.0,274baa43b0e13e37fafa6428dbc7938e62e5c439 +jinaai/jina-reranker-v2-base-multilingual,,29,CrossEncoder,float32,sdpa,FAIL(load),load_cpu,,,,,,,,9cfeff2df7d40d1b78e75e5e9cebec92a99813c9 +thenlper/gte-small,,30,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.430511474609375e-06,0.22466376516968012,24.0,17e1f347d17fe144873b1201da91788898c639cd +sentence-transformers/paraphrase-mpnet-base-v2,,31,SentenceTransformer,float32,eager,PASS,,2,2,True,True,1.1920928955078125e-07,0.562696953304112,24.0,6cc9279c672dc57f94445ef259b28a1b736fec8f +sentence-transformers/distiluse-base-multilingual-cased-v1,,33,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,4.76837158203125e-07,0.6170224482193589,24.0,826fee3d516ebb14987355af373f5b69101c7006 +sentence-transformers/multi-qa-mpnet-base-dot-v1,,34,SentenceTransformer,float32,eager,FAIL(forward),neuron_inference,2,,,,,0.5608947025611997,24.0,17997f24dca0df1a4fed68894fb0e1e133e60482 +sentence-transformers/paraphrase-MiniLM-L6-v2,,35,SentenceTransformer,float32,sdpa,FAIL(output),,3,3,False,True,1.1920928955078125e-07,0.20903876516968012,24.0,c9a2bfebc254878aee8c3aca9e6844d5bbb102d1 +jinaai/jina-embeddings-v2-small-en,,38,SentenceTransformer,float32,sdpa,FAIL(load),load_cpu,,,,,,,,44e7d1d6caec8c883c2d4b207588504d519788d0 +WhereIsAI/UAE-Large-V1,,41,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,4.76837158203125e-07,1.361337617971003,24.0,9c9b2c999b3350cfb3171ed429320668e39b00b8 +jhgan/ko-sroberta-multitask,,42,SentenceTransformer,float32,sdpa,FAIL(output),,4,4,False,True,1.1920928955078125e-07,0.5631938884034753,24.0,8fca7c9c98c26599be0e14b9916b11a756a26f19 +cross-encoder/ms-marco-MiniLM-L12-v2,,43,CrossEncoder,float32,sdpa,PASS,,2,2,True,True,5.245208740234375e-06,0.21909079421311617,24.0,7b0235231ca2674cb8ca8f022859a6eba2b1c968 +intfloat/e5-small-v2,,44,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,5.960464477539062e-07,0.22467234823852777,24.0,ffb93f3bd4047442299a41ebb6fa998a38507c52 +intfloat/e5-base-v2,,45,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.5497207641601562e-06,0.549919799901545,24.0,f52bf8ec8c7124536f0efb74aca902b2995e5bcd +deepvk/USER2-base,,46,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,7.152557373046875e-07,0.6779180848971009,24.0,94bbff0cc696f26dc93b275fc874657727df0c29 +intfloat/e5-base,,47,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,6.556510925292969e-07,0.5499312439933419,24.0,b533fe4636f4a2507c08ddab40644d20b0006d6a +sentence-transformers-testing/stsb-bert-tiny-safetensors,,49,SentenceTransformer,float32,sdpa,FAIL(output),,4,4,False,True,2.980232238769531e-07,0.10120703373104334,24.0,f3cb857cba53019a20df283396bcca179cf051a4 +Alibaba-NLP/gte-multilingual-base,,50,SentenceTransformer,float32,sdpa,FAIL(forward),cpu_inference,,,,,,,,9bbca17d9273fd0d03d5725c7a4b0f6b45142062 +sentence-transformers/distiluse-base-multilingual-cased-v2,,51,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,4.76837158203125e-07,0.6170224482193589,24.0,bfe45d0732ca50787611c0fe107ba278c7f3f889 +NeuML/pubmedbert-base-embeddings,,52,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,4.76837158203125e-07,0.549232610501349,24.0,b79526d6ef3645e0df4530322e266f24c829f5ef +shibing624/text2vec-base-chinese,,53,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,3.8743019104003906e-07,0.5224064150825143,24.0,183bb99aa7af74355fb58d16edf8c13ae7c5433e +bkai-foundation-models/vietnamese-bi-encoder,,55,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.0132789611816406e-06,0.6530109951272607,24.0,84f9d9ada0d1a3c37557398b9ae9fcedcdf40be0 +nomic-ai/nomic-embed-text-v1,,57,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.3113021850585938e-06,0.6793373385444283,24.0,3ac47f125a41961d13b397d0332866be2f9152e1 +nomic-ai/nomic-embed-text-v2-moe,,58,SentenceTransformer,float32,sdpa,FAIL(forward),cpu_inference,,,,,,,,1066b6599d099fbb93dfcb64f9c37a7c9e503e85 +intfloat/e5-large-v2,,59,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.3113021850585938e-06,1.361520134843886,24.0,f169b11e22de13617baa190a028a32f3493550b6 +sentence-transformers/paraphrase-MiniLM-L3-v2,,60,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,4.76837158203125e-07,0.20122626516968012,24.0,4ca70771034acceecb2e72475f72050fcdde4ddc +mixedbread-ai/mxbai-rerank-xsmall-v1,,61,CrossEncoder,float32,eager,PASS,,2,2,True,True,2.980232238769531e-07,0.43770044296979904,24.0,b5c6e9da73abc3711f593f705371cdbe9e0fe422 +sentence-transformers/multi-qa-MiniLM-L6-cos-v1,,63,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,7.152557373046875e-07,0.20904353354126215,24.0,b207367332321f8e44f96e224ef15bc607f4dbf0 +thenlper/gte-large,,64,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,1.430511474609375e-06,1.361499154008925,24.0,4bef63f39fcc5e2d6b0aae83089f307af4970164 +Snowflake/snowflake-arctic-embed-l,,65,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,6.556510925292969e-07,1.3595066079869866,24.0,d8fb21ca8d905d2832ee8b96c894d3298964346b +sentence-transformers/all-roberta-large-v1,,66,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,7.748603820800781e-07,1.4425214165821671,24.0,cf74d8acd4f198de950bf004b262e6accfed5d2c +sentence-transformers/msmarco-bert-base-dot-v5,,68,SentenceTransformer,float32,sdpa,FAIL(forward),neuron_inference,2,,,,,0.5481633553281426,24.0,dbf04e3911e5b11c887fe563d3f2479f81c4415f +TencentBAC/Conan-embedding-v1,,69,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,2.384185791015625e-07,1.3289961153641343,24.0,bb9749a57d4f02fd71722386f8d0f5a9398d7eeb +cross-encoder/ms-marco-TinyBERT-L2-v2,,70,CrossEncoder,float32,sdpa,PASS,,2,2,True,True,1.5735626220703125e-05,0.09424082655459642,24.0,81d1926f67cb8eee2c2be17ca9f793c7c3bd20cc +Alibaba-NLP/gte-base-en-v1.5,,71,SentenceTransformer,float32,sdpa,FAIL(forward),cpu_inference,,,,,,,,a829fd0e060bb84554da0dfd354d0de0f7712b7f +emrecan/bert-base-turkish-cased-mean-nli-stsb-tr,,72,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,2.384185791015625e-07,0.5535542676225305,24.0,7e10e2fbd7627fd0228eb2dbdc9e9da264442bbe +sentence-transformers/paraphrase-albert-small-v2,,73,SentenceTransformer,float32,sdpa,PASS,,2,2,True,True,2.384185791015625e-07,0.17103421781212091,24.0,9d490b476eb5291c7885bb6d4961318740493cf2 +sentence-transformers/nli-mpnet-base-v2,,74,SentenceTransformer,float32,eager,PASS,,2,2,True,True,1.7881393432617188e-07,0.5626959996297956,24.0,c2f4dd9a1dc4337c28cfbd650433f761bb304c50 +minishlab/potion-base-8M,,75,SentenceTransformer,float32,sdpa,FAIL(output),,3,3,False,True,5.364418029785156e-07,0.03770802170038223,24.0,bf8b056651a2c21b8d2565580b8569da283cab23 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Visit https://huggingface.co/litert-community/embeddinggemma-300m to ask for access.", + "traceback": "httpx.HTTPStatusError: Client error '403 Forbidden' for url 'https://huggingface.co/litert-community/embeddinggemma-300m/resolve/459f1d37fec9635eb1730ebdbc219bfc3226c8e7/modules.json'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/403\n\nThe above exception was the direct cause of the following exception:\n\nTraceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/023/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1190, in _load_modules\n modules_json_path = load_file_path(\n model_name_or_path,\n ...<4 lines>...\n local_files_only=local_files_only,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/file_io.py\", line 208, in load_file_path\n return hf_hub_download(\n model_name_or_path,\n ...<6 lines>...\n local_files_only=local_files_only,\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/utils/_validators.py\", line 89, in _inner_fn\n return fn(*args, **kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/utils/_http.py\", line 266, in _inner\n return fn(*args, **kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py\", line 1047, in hf_hub_download\n return _hf_hub_download_to_cache_dir(\n # Destination\n ...<15 lines>...\n dry_run=dry_run,\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py\", line 1194, in _hf_hub_download_to_cache_dir\n _raise_on_head_call_error(head_call_error, force_download, local_files_only)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py\", line 1953, in _raise_on_head_call_error\n raise head_call_error\nhuggingface_hub.errors.GatedRepoError: 403 Client Error. (Request ID: Root=1-6ae9fe77-5b99b3f12170976f33af1862;24fb7211-ac04-4557-9d7c-d58c3b8e6212)\n\nCannot access gated repo for url https://huggingface.co/litert-community/embeddinggemma-300m/resolve/459f1d37fec9635eb1730ebdbc219bfc3226c8e7/modules.json.\nAccess to model litert-community/embeddinggemma-300m is restricted and you are not in the authorized list. Visit https://huggingface.co/litert-community/embeddinggemma-300m to ask for access.\n", + "result": "FAIL(load)", + "total_seconds": 8.972315741702914, + "prior_attempts": [] + }, + { + "index": 24, + "model": "Qwen/Qwen3-VL-Embedding-8B", + "revision": "2c4565515e0f265c6511776e7193b22c0968ddc7", + "trending_rank": 24, + "downloads_rank": 54, + "class": "SentenceTransformer", + "dtype": "bfloat16", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:32:09.263638+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 45.57155937794596, + "prompts": { + "query": "", + "document": "", + "default": "Represent the user's input." + }, + "parameter_dtypes": [ + "torch.bfloat16" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.5104122161865234, + 0.8333847522735596, + 0.5737250447273254, + 0.6311128735542297 + ], + "cpu_seconds": 11.08764569554478, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 30.12761875614524, + "neuron_scores": [ + 0.5109585523605347, + 0.8327626585960388, + 0.5716332197189331, + 0.6295062899589539 + ], + "max_abs_error": 0.002091825008392334, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": false, + "neuron_repeat_seconds": 0.4174205930903554, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "FAIL(output)", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 330, + "sample_interval_seconds": 0.1, + "peak_bytes": 16529538997, + "peak_categories": { + "code": 14566248, + "tensors": 16414412800, + "constants": 4571149, + "scratchpad": 67108864, + "misc": 24082496, + "dma_rings": 4797440 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 16390182848, + "allocator_peak_reserved_bytes": 16414408704, + "total_seconds": 119.78512970823795, + "prior_attempts": [] + }, + { + "index": 25, + "model": "Octen/Octen-Embedding-0.6B", + "revision": "b54faa2ba2ae9eb618f88526cec6dae3287eb5f8", + "trending_rank": 25, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:32:54.188085+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 11.22696934826672, + "prompts": { + "query": "Instruct: Given a web search query, retrieve relevant passages that answer the query\nQuery:", + "document": " " + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.5048121213912964, + 0.7934467196464539, + 0.6662667989730835, + 0.7119179964065552 + ], + "cpu_seconds": 0.483399904333055, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 36.68452943768352, + "neuron_scores": [ + 0.5048115253448486, + 0.7934461832046509, + 0.6662657260894775, + 0.7119169235229492 + ], + "max_abs_error": 1.0728836059570312e-06, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.37421242613345385, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 374, + "sample_interval_seconds": 0.1, + "peak_bytes": 2554741801, + "peak_categories": { + "code": 9892184, + "tensors": 2443186176, + "constants": 5668881, + "scratchpad": 67108864, + "misc": 21301696, + "dma_rings": 7584000 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 2390247296, + "allocator_peak_reserved_bytes": 2443182080, + "total_seconds": 88.97745289001614, + "prior_attempts": [] + }, + { + "index": 26, + "model": "ibm-granite/granite-embedding-311m-multilingual-r2", + "revision": "44399559930365213510b1ee2eb15ded83374f0e", + "trending_rank": 26, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:33:41.606766+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 8.105422412976623, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.8707175850868225, + 0.9430661797523499, + 0.9223527312278748, + 0.9145148992538452 + ], + "cpu_seconds": 0.12631676066666842, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 110.7295867903158, + "neuron_scores": [ + 0.87071692943573, + 0.9430654644966125, + 0.9223518967628479, + 0.914514422416687 + ], + "max_abs_error": 8.344650268554688e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.09659209195524454, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 1110, + "sample_interval_seconds": 0.1, + "peak_bytes": 1377887889, + "peak_categories": { + "code": 7370752, + "tensors": 1283461120, + "constants": 3801105, + "scratchpad": 67108864, + "misc": 13895296, + "dma_rings": 2250752 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 1274030464, + "allocator_peak_reserved_bytes": 1283457024, + "total_seconds": 138.50174752250314, + "prior_attempts": [] + }, + { + "index": 27, + "model": "unsloth/embeddinggemma-2", + "revision": "c8f89cc7ecb4ba5122cd15fdd487422b2b487daf", + "trending_rank": 27, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": { + "vision_config": null, + "audio_config": null + }, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:33:42.702445+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 4.934092523530126, + "prompts": { + "query": "task: search result | query: ", + "document": "title: none | text: ", + "BitextMining": "task: search result | query: ", + "Classification": "task: classification | query: ", + "Clustering": "task: clustering | query: ", + "CodeRetrieval": "task: code retrieval | query: ", + "Document": "title: none | text: ", + "FactChecking": "task: fact checking | query: ", + "InstructionRetrieval": "task: code retrieval | query: ", + "MultilabelClassification": "task: classification | query: ", + "PairClassification": "task: sentence similarity | query: ", + "QuestionAnswering": "task: question answering | query: ", + "Reranking": "task: search result | query: ", + "Retrieval": "task: search result | query: ", + "Retrieval-document": "title: none | text: ", + "Retrieval-query": "task: search result | query: ", + "STS": "task: sentence similarity | query: ", + "SearchQuery": "task: search result | query: ", + "SentenceSimilarity": "task: sentence similarity | query: ", + "Summarization": "task: sentence similarity | query: " + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.6754717230796814, + 0.8531962037086487, + 0.7467769980430603, + 0.778255820274353 + ], + "cpu_seconds": 0.23618513904511929, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 1.7631996544077992, + "neuron_scores": [ + 0.6754712462425232, + 0.8531948328018188, + 0.7467760443687439, + 0.7782547473907471 + ], + "max_abs_error": 1.3709068298339844e-06, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.2790237655863166, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 23, + "sample_interval_seconds": 0.1, + "peak_bytes": 1316233881, + "peak_categories": { + "code": 14610624, + "tensors": 1176506368, + "constants": 13434905, + "scratchpad": 67108864, + "misc": 39161536, + "dma_rings": 5411584 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 1105258368, + "allocator_peak_reserved_bytes": 1176502272, + "total_seconds": 25.065962282940745, + "prior_attempts": [] + }, + { + "index": 28, + "model": "nvidia/Nemotron-3.5-Embed-8B-BF16", + "revision": "781e779ee4ca9c2d2a4f38321993556baeab49a1", + "trending_rank": 28, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "bfloat16", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:34:09.839866+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 30.307704116217792, + "prompts": { + "query": "query: ", + "document": "passage: " + }, + "parameter_dtypes": [ + "torch.bfloat16" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.20129865407943726, + 0.6487177014350891, + 0.3337305784225464, + 0.39611101150512695 + ], + "cpu_seconds": 21.436434123665094, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 78.27636251132935, + "neuron_scores": [ + 0.20180511474609375, + 0.6485709547996521, + 0.3331759572029114, + 0.39626163244247437 + ], + "max_abs_error": 0.0005546212196350098, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.32933425810188055, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 808, + "sample_interval_seconds": 0.1, + "peak_bytes": 16963532173, + "peak_categories": { + "code": 14068608, + "tensors": 16854814720, + "constants": 4292621, + "scratchpad": 67108864, + "misc": 21104128, + "dma_rings": 2143232 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 16784201856, + "allocator_peak_reserved_bytes": 16854810624, + "total_seconds": 166.1292742099613, + "prior_attempts": [] + }, + { + "index": 29, + "model": "BrunoHays/embeddinggemma-2-nullspace-audio", + "revision": "4e54c6816e4ba368be62885788974458f2748adf", + "trending_rank": 29, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:34:11.569070+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ValueError", + "error": "Unrecognized model in BrunoHays/embeddinggemma-2-nullspace-audio. Should have a `model_type` key in its config.json.", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/029/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1200, in _load_modules\n return self._load_default_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 1272, in _load_default_modules\n transformer_model = Transformer(\n model_name_or_path,\n ...<4 lines>...\n backend=self.backend,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 839, in __init__\n config, is_peft_model = self._load_config(model_name_or_path, backend, config_kwargs)\n ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2259, in _load_config\n return AutoConfig.from_pretrained(model_name_or_path, **config_kwargs), False\n ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/configuration_auto.py\", line 450, in from_pretrained\n raise ValueError(\n ...<2 lines>...\n )\nValueError: Unrecognized model in BrunoHays/embeddinggemma-2-nullspace-audio. Should have a `model_type` key in its config.json.\n", + "result": "FAIL(load)", + "total_seconds": 24.265914521180093, + "prior_attempts": [] + }, + { + "index": 30, + "model": "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2", + "revision": "e8f8c211226b894fcb81acc59f3b34ba3efd5f42", + "trending_rank": 30, + "downloads_rank": 5, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:34:25.424009+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 2.329072717577219, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.4534403681755066, + 0.7260404229164124, + 0.636457622051239, + 0.6645654439926147 + ], + "cpu_seconds": 0.33260378241539, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 0.36306043714284897, + "neuron_scores": [ + 0.4534405469894409, + 0.7260406017303467, + 0.6364576816558838, + 0.6645653247833252 + ], + "max_abs_error": 1.7881393432617188e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.050801802426576614, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 8, + "sample_interval_seconds": 0.1, + "peak_bytes": 579133161, + "peak_categories": { + "code": 6422360, + "tensors": 490737664, + "constants": 3047441, + "scratchpad": 67108864, + "misc": 9458048, + "dma_rings": 2358784 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 482097920, + "allocator_peak_reserved_bytes": 490733568, + "total_seconds": 54.63676546048373, + "prior_attempts": [] + }, + { + "index": 31, + "model": "BAAI/bge-reranker-v2-gemma", + "revision": "1787044f8b6fb740a9de4557c3a12377f84d9e17", + "trending_rank": 31, + "downloads_rank": null, + "class": "CrossEncoder", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:34:37.563999+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 6.2028824258595705, + "prompts": {}, + "parameter_dtypes": [ + "torch.float32" + ], + "cpu_scores": [ + 0.9997572302818298, + 0.9997515082359314, + 0.9998114705085754, + 0.9997087121009827 + ], + "cpu_seconds": 32.531744067557156, + "cpu_top_document": 3, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 45.031333486549556, + "neuron_scores": [ + 0.9997572898864746, + 0.9997514486312866, + 0.9998114109039307, + 0.9997087717056274 + ], + "max_abs_error": 5.960464477539063e-08, + "neuron_top_document": 3, + "mars_first": false, + "cpu_parity": true, + "neuron_repeat_seconds": 0.09113490767776966, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "FAIL(output)", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 460, + "sample_interval_seconds": 0.1, + "peak_bytes": 10210461645, + "peak_categories": { + "code": 20083904, + "tensors": 10112471040, + "constants": 1474573, + "scratchpad": 67108864, + "misc": 8413952, + "dma_rings": 909312 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 10061462720, + "allocator_peak_reserved_bytes": 10112466944, + "total_seconds": 123.40695661306381, + "prior_attempts": [] + }, + { + "index": 32, + "model": "Snowflake/snowflake-arctic-embed-m", + "revision": "fc74610d18462d218e312aa986ec5c8a75a98152", + "trending_rank": 32, + "downloads_rank": 87, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:35:22.791500+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 2.8294941186904907, + "prompts": { + "query": "Represent this sentence for searching relevant passages: ", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.29497820138931274, + 0.46003827452659607, + 0.37610626220703125, + 0.37524640560150146 + ], + "cpu_seconds": 0.20452320855110884, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 122.39083545841277, + "neuron_scores": [ + 0.29497796297073364, + 0.4600379168987274, + 0.37610629200935364, + 0.3752461373806 + ], + "max_abs_error": 3.5762786865234375e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.06222762539982796, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 1225, + "sample_interval_seconds": 0.1, + "peak_bytes": 588789497, + "peak_categories": { + "code": 6324264, + "tensors": 501223424, + "constants": 2850833, + "scratchpad": 67108864, + "misc": 8641472, + "dma_rings": 2640640 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 479321920, + "allocator_peak_reserved_bytes": 501219328, + "total_seconds": 190.96402557753026, + "prior_attempts": [] + }, + { + "index": 33, + "model": "Snowflake/snowflake-arctic-embed-m-v2.0", + "revision": "95c2741480856aa9666782eb4afe11959938017f", + "trending_rank": 33, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": { + "use_memory_efficient_attention": false, + "unpad_inputs": false + }, + "excluded": null, + "exclusion": null, + "reason": "Checkpoint custom code supports standard SDPA when xformers attention and input unpadding are disabled.", + "started_at": "2026-11-03T16:00:36.977122+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 3.8345429748296738, + "prompts": { + "query": "query: ", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "status": "error", + "stage": "cpu_inference", + "error_type": "IndexError", + "error": "index 140493294592752 is out of bounds for dimension 0 with size 14", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/033/run.py\", line 64, in \n stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/033/run.py\", line 59, in score\n q=(model.encode([query],batch_size=4,show_progress_bar=False,**kw,**SPEC['query_kwargs']) if SPEC.get('query_kwargs') else model.encode_query([query],batch_size=4,show_progress_bar=False,**kw))\n ~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 370, in encode_query\n return self.encode(\n ~~~~~~~~~~~^\n inputs=inputs,\n ^^^^^^^^^^^^^^\n ...<14 lines>...\n **kwargs,\n ^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 895, in encode\n all_embeddings = self._inference(inputs, device=device, **inference_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 963, in _inference\n out_features = self(features, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 600, in forward\n input = module(input, **module_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 1647, in forward\n model_output = model_method(**filtered_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Snowflake/snowflake_hyphen_arctic_hyphen_embed_hyphen_m_hyphen_v2_dot_0/95c2741480856aa9666782eb4afe11959938017f/modeling_hf_alibaba_nlp_gte.py\", line 900, in forward\n (embedding_output, attention_mask, rope_embeds, length) = self.embeddings(\n ~~~~~~~~~~~~~~~^\n unpad_inputs,\n ^^^^^^^^^^^^^\n ...<5 lines>...\n inputs_embeds=inputs_embeds\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Snowflake/snowflake_hyphen_arctic_hyphen_embed_hyphen_m_hyphen_v2_dot_0/95c2741480856aa9666782eb4afe11959938017f/modeling_hf_alibaba_nlp_gte.py\", line 391, in forward\n rope_cos = rope_cos[position_ids].unsqueeze(2) # [bs, seq_len, 1, dim]\n ~~~~~~~~^^^^^^^^^^^^^^\nIndexError: index 140493294592752 is out of bounds for dimension 0 with size 14\n", + "result": "FAIL(forward)", + "total_seconds": 12.881709131412208, + "prior_attempts": [ + { + "index": 33, + "model": "Snowflake/snowflake-arctic-embed-m-v2.0", + "revision": "95c2741480856aa9666782eb4afe11959938017f", + "trending_rank": 33, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:36:02.649580+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "AssertionError", + "error": "please install xformers", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/033/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 855, in __init__\n self.model = self._load_model(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2343, in _load_model\n return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 389, in from_pretrained\n return model_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4300, in from_pretrained\n model = cls(config, *model_args, **model_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Snowflake/snowflake_hyphen_arctic_hyphen_embed_hyphen_m_hyphen_v2_dot_0/95c2741480856aa9666782eb4afe11959938017f/modeling_hf_alibaba_nlp_gte.py\", line 837, in __init__\n self.encoder = GteEncoder(config)\n ~~~~~~~~~~^^^^^^^^\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Snowflake/snowflake_hyphen_arctic_hyphen_embed_hyphen_m_hyphen_v2_dot_0/95c2741480856aa9666782eb4afe11959938017f/modeling_hf_alibaba_nlp_gte.py\", line 706, in __init__\n self.layer = nn.ModuleList([GteLayer(config) for _ in range(config.num_hidden_layers)])\n ~~~~~~~~^^^^^^^^\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Snowflake/snowflake_hyphen_arctic_hyphen_embed_hyphen_m_hyphen_v2_dot_0/95c2741480856aa9666782eb4afe11959938017f/modeling_hf_alibaba_nlp_gte.py\", line 640, in __init__\n self.attention = GTE_ATTENTION_CLASSES[attn_implementation](\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n config, pack_qkv=pack_qkv, use_memory_efficient_attention=use_memory_efficient_attention\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Snowflake/snowflake_hyphen_arctic_hyphen_embed_hyphen_m_hyphen_v2_dot_0/95c2741480856aa9666782eb4afe11959938017f/modeling_hf_alibaba_nlp_gte.py\", line 454, in __init__\n assert self.memory_efficient_attention is not None, 'please install xformers'\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError: please install xformers\n", + "result": "FAIL(load)", + "total_seconds": 29.104860222898424 + } + ] + }, + { + "index": 34, + "model": "Qwen/Qwen3-Reranker-8B", + "revision": "77d193c791ed757ca307ee72715aa132723da912", + "trending_rank": 34, + "downloads_rank": null, + "class": "CrossEncoder", + "dtype": "bfloat16", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:36:33.649395+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 8.139716992154717, + "prompts": { + "query": "Given a web search query, retrieve relevant passages that answer the query" + }, + "parameter_dtypes": [ + "torch.bfloat16" + ], + "cpu_scores": [ + -8.125, + 4.0625, + -5.34375, + -4.5625 + ], + "cpu_seconds": 24.723026665858924, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 59.1664319653064, + "neuron_scores": [ + -8.0625, + 4.0625, + -5.375, + -4.5625 + ], + "max_abs_error": 0.0625, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": false, + "neuron_repeat_seconds": 0.24539023637771606, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "FAIL(output)", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 621, + "sample_interval_seconds": 0.1, + "peak_bytes": 19178892667, + "peak_categories": { + "code": 25923376, + "tensors": 16521367552, + "constants": 1425419, + "scratchpad": 2617245696, + "misc": 11091520, + "dma_rings": 1839104 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 16468168832, + "allocator_peak_reserved_bytes": 16521363456, + "total_seconds": 126.22209540009499, + "prior_attempts": [] + }, + { + "index": 35, + "model": "Qwen/Qwen3-Embedding-4B", + "revision": "5cf2132abc99cad020ac570b19d031efec650f2b", + "trending_rank": 35, + "downloads_rank": 24, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:36:43.945759+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 16.116954929195344, + "prompts": { + "query": "Instruct: Given a web search query, retrieve relevant passages that answer the query\nQuery:", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.3845120668411255, + 0.6771758794784546, + 0.5112091302871704, + 0.4612208902835846 + ], + "cpu_seconds": 3.889276017434895, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 79.5975486394018, + "neuron_scores": [ + 0.3845122456550598, + 0.6771759986877441, + 0.5112086534500122, + 0.4612205922603607 + ], + "max_abs_error": 4.76837158203125e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.41087701451033354, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 817, + "sample_interval_seconds": 0.1, + "peak_bytes": 16479713697, + "peak_categories": { + "code": 12875472, + "tensors": 16368275456, + "constants": 5603345, + "scratchpad": 67108864, + "misc": 21263552, + "dma_rings": 4587008 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 16111990784, + "allocator_peak_reserved_bytes": 16368271360, + "total_seconds": 130.10293987672776, + "prior_attempts": [] + }, + { + "index": 36, + "model": "nvidia/llama-nemotron-rerank-vl-1b-v2", + "revision": "b8a9987b05b75db5ad949c825cbcbf6eb7c48b5a", + "trending_rank": 36, + "downloads_rank": null, + "class": "CrossEncoder", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:36:58.723986+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 8.254427562467754, + "prompts": {}, + "parameter_dtypes": [ + "torch.float32" + ], + "cpu_scores": [ + -4.155534744262695, + 4.602201461791992, + -1.6747599840164185, + -0.08092916011810303 + ], + "cpu_seconds": 1.1451246766373515, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 91.10596974659711, + "neuron_scores": [ + -4.155538558959961, + 4.602203845977783, + -1.6747604608535767, + -0.08092620968818665 + ], + "max_abs_error": 3.814697265625e-06, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.07034432422369719, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 918, + "sample_interval_seconds": 0.1, + "peak_bytes": 7049644197, + "peak_categories": { + "code": 7378648, + "tensors": 6960451584, + "constants": 2752525, + "scratchpad": 67108864, + "misc": 10031552, + "dma_rings": 1921024 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 6921330368, + "allocator_peak_reserved_bytes": 6960447488, + "total_seconds": 162.6410767203197, + "prior_attempts": [] + }, + { + "index": 37, + "model": "Octen/Octen-Embedding-8B", + "revision": "88695e4f8ed87b4ce08df2fea6ff25bfe0f9875b", + "trending_rank": 37, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "bfloat16", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:38:36.312159+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 11.599875870160758, + "prompts": { + "query": "Instruct: Given a web search query, retrieve relevant passages that answer the query\nQuery:", + "document": " " + }, + "parameter_dtypes": [ + "torch.bfloat16" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.42542529106140137, + 0.8571639060974121, + 0.5231301784515381, + 0.5200198292732239 + ], + "cpu_seconds": 17.96875706128776, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 27.91108343563974, + "neuron_scores": [ + 0.4267808794975281, + 0.8579877018928528, + 0.5234858989715576, + 0.5211225152015686 + ], + "max_abs_error": 0.001355588436126709, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.5253493608906865, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 313, + "sample_interval_seconds": 0.1, + "peak_bytes": 15325923085, + "peak_categories": { + "code": 14376512, + "tensors": 15210647552, + "constants": 3833869, + "scratchpad": 67108864, + "misc": 22354880, + "dma_rings": 7601408 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 15147458112, + "allocator_peak_reserved_bytes": 15210643456, + "total_seconds": 93.45890662632883, + "prior_attempts": [] + }, + { + "index": 38, + "model": "Octen/Octen-Embedding-4B", + "revision": "dcfdcdaf02e2f4fc26a22ee36936b2afcad8b208", + "trending_rank": 38, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:38:41.994144+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 18.089695871807635, + "prompts": { + "query": "Instruct: Given a web search query, retrieve relevant passages that answer the query\nQuery:", + "document": " " + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.5158511400222778, + 0.8830810189247131, + 0.6787099838256836, + 0.6655396223068237 + ], + "cpu_seconds": 3.1818364039063454, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 26.612441043369472, + "neuron_scores": [ + 0.5158512592315674, + 0.883080005645752, + 0.6787102222442627, + 0.6655394434928894 + ], + "max_abs_error": 1.0132789611816406e-06, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.52085015270859, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 295, + "sample_interval_seconds": 0.1, + "peak_bytes": 16481455145, + "peak_categories": { + "code": 13330904, + "tensors": 16366178304, + "constants": 5603345, + "scratchpad": 67108864, + "misc": 21238080, + "dma_rings": 7995648 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 16108736256, + "allocator_peak_reserved_bytes": 16366174208, + "total_seconds": 85.57725712750107, + "prior_attempts": [] + }, + { + "index": 39, + "model": "Octen/Octen-Embedding-8B-INT8", + "revision": "2220d20a1720017df6a352884c0c3099aed8de15", + "trending_rank": 39, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "bfloat16", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": "Quantized checkpoint requires a quantization backend outside this native floating-point Neuron sweep.", + "exclusion": "quantized", + "result": "EXCLUDED", + "status": "excluded", + "notes": "Quantized checkpoint requires a quantization backend outside this native floating-point Neuron sweep." + }, + { + "index": 40, + "model": "jinaai/jina-embeddings-v5-text-small", + "revision": "dd76d535f5447ca3897a9c893fb1e612ead98192", + "trending_rank": 40, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "query_kwargs": { + "task": "retrieval", + "prompt_name": "query" + }, + "document_kwargs": { + "task": "retrieval", + "prompt_name": "document" + }, + "reason": "Use model-card retrieval task and prompts with encode().", + "started_at": "2026-11-03T16:00:36.968030+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 3.2578425342217088, + "prompts": { + "query": "Query: ", + "document": "Document: " + }, + "parameter_dtypes": [ + "torch.bfloat16", + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.4861639738082886, + 0.761303722858429, + 0.5923711657524109, + 0.6189237236976624 + ], + "cpu_seconds": 0.5321778431534767, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 55.49857556447387, + "neuron_scores": [ + 0.48602616786956787, + 0.761559247970581, + 0.5916945338249207, + 0.6193601489067078 + ], + "max_abs_error": 0.0006766319274902344, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.4596897279843688, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 562, + "sample_interval_seconds": 0.1, + "peak_bytes": 1708037221, + "peak_categories": { + "code": 11276632, + "tensors": 1593839616, + "constants": 6258701, + "scratchpad": 67108864, + "misc": 26169088, + "dma_rings": 3384320 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 1533175616, + "allocator_peak_reserved_bytes": 1593835520, + "total_seconds": 75.5987659515813, + "prior_attempts": [ + { + "index": 40, + "model": "jinaai/jina-embeddings-v5-text-small", + "revision": "dd76d535f5447ca3897a9c893fb1e612ead98192", + "trending_rank": 40, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:38:57.389433+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 6.557366493158042, + "prompts": { + "query": "Query: ", + "document": "Document: " + }, + "parameter_dtypes": [ + "torch.bfloat16", + "torch.float32" + ], + "status": "error", + "stage": "cpu_inference", + "error_type": "ValueError", + "error": "Invalid task: query. Must be one of ['retrieval', 'text-matching', 'clustering', 'classification'].", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/040/run.py\", line 63, in \n stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/040/run.py\", line 58, in score\n q=model.encode_query([query],batch_size=4,show_progress_bar=False,**kw)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 370, in encode_query\n return self.encode(\n ~~~~~~~~~~~^\n inputs=inputs,\n ^^^^^^^^^^^^^^\n ...<14 lines>...\n **kwargs,\n ^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 895, in encode\n all_embeddings = self._inference(inputs, device=device, **inference_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 963, in _inference\n out_features = self(features, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 600, in forward\n input = module(input, **module_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_embeddings_hyphen_v5_hyphen_text_hyphen_small/dd76d535f5447ca3897a9c893fb1e612ead98192/custom_st.py\", line 83, in forward\n raise ValueError(\n f\"Invalid task: {task}. Must be one of {self.config.task_names}.\"\n )\nValueError: Invalid task: query. Must be one of ['retrieval', 'text-matching', 'clustering', 'classification'].\n", + "result": "FAIL(forward)", + "total_seconds": 75.6422152929008 + } + ] + }, + { + "index": 41, + "model": "microsoft/harrier-oss-v1-270m", + "revision": "31de22b673913c7d658c0f03f792d77c2dcf8ebd", + "trending_rank": 41, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:39:43.398351+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 3.0636923322454095, + "prompts": { + "query": "", + "document": "", + "web_search_query": "Instruct: Given a web search query, retrieve relevant passages that answer the query\nQuery: ", + "sts_query": "Instruct: Retrieve semantically similar text\nQuery: ", + "bitext_query": "Instruct: Retrieve parallel sentences\nQuery: " + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.5037330985069275, + 0.6896124482154846, + 0.5988523960113525, + 0.5813120007514954 + ], + "cpu_seconds": 0.10757879540324211, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 77.40132252499461, + "neuron_scores": [ + 0.5037326812744141, + 0.6896117925643921, + 0.5988525152206421, + 0.5813115835189819 + ], + "max_abs_error": 6.556510925292969e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.28434949833899736, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 777, + "sample_interval_seconds": 0.1, + "peak_bytes": 1212426313, + "peak_categories": { + "code": 9520696, + "tensors": 1103106048, + "constants": 6062097, + "scratchpad": 67108864, + "misc": 20648192, + "dma_rings": 5980416 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 1075587840, + "allocator_peak_reserved_bytes": 1103101952, + "total_seconds": 112.00472678616643, + "prior_attempts": [] + }, + { + "index": 42, + "model": "jinaai/jina-embeddings-v5-omni-small", + "revision": "950200abde3a3bcf3d5bdfe5d28fb5bb5e7dfbb0", + "trending_rank": 42, + "downloads_rank": 48, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "extra_model_kwargs": { + "default_task": "retrieval" + }, + "reason": "Select the retrieval adapter as required by the model card.", + "started_at": "2026-11-03T16:00:36.976906+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 4.060450030490756, + "prompts": { + "query": "Query: ", + "document": "Document: " + }, + "parameter_dtypes": [ + "torch.bfloat16", + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.4861639738082886, + 0.761303722858429, + 0.5923711657524109, + 0.6189237236976624 + ], + "cpu_seconds": 0.45869939867407084, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 53.69139523431659, + "neuron_scores": [ + 0.48602616786956787, + 0.761559247970581, + 0.5916945338249207, + 0.6193601489067078 + ], + "max_abs_error": 0.0006766319274902344, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.5224980432540178, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 549, + "sample_interval_seconds": 0.1, + "peak_bytes": 5587684101, + "peak_categories": { + "code": 11797496, + "tensors": 5469376512, + "constants": 6782989, + "scratchpad": 67108864, + "misc": 28615424, + "dma_rings": 4002816 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 5277416064, + "allocator_peak_reserved_bytes": 5469372416, + "total_seconds": 76.29171908739954, + "prior_attempts": [ + { + "index": 42, + "model": "jinaai/jina-embeddings-v5-omni-small", + "revision": "950200abde3a3bcf3d5bdfe5d28fb5bb5e7dfbb0", + "trending_rank": 42, + "downloads_rank": 48, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:40:10.822178+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 10.483749182894826, + "prompts": { + "query": "Query: ", + "document": "Document: " + }, + "parameter_dtypes": [ + "torch.bfloat16", + "torch.float32" + ], + "status": "error", + "stage": "cpu_inference", + "error_type": "ValueError", + "error": "Task must be specified. Set it during loading (model_kwargs={'default_task': 'retrieval'}) or pass task='retrieval' to encode().", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/042/run.py\", line 63, in \n stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/042/run.py\", line 58, in score\n q=model.encode_query([query],batch_size=4,show_progress_bar=False,**kw)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_embeddings_hyphen_v5_hyphen_omni_hyphen_small/950200abde3a3bcf3d5bdfe5d28fb5bb5e7dfbb0/custom_st.py\", line 545, in encode_query\n return self.encode(sentences, *args, **kwargs)\n ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_embeddings_hyphen_v5_hyphen_omni_hyphen_small/950200abde3a3bcf3d5bdfe5d28fb5bb5e7dfbb0/custom_st.py\", line 528, in _encode\n result = _orig(self, sentences, *args, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 895, in encode\n all_embeddings = self._inference(inputs, device=device, **inference_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 963, in _inference\n out_features = self(features, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 600, in forward\n input = module(input, **module_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_embeddings_hyphen_v5_hyphen_omni_hyphen_small/950200abde3a3bcf3d5bdfe5d28fb5bb5e7dfbb0/custom_st.py\", line 897, in forward\n task = self._resolve_task(task)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_embeddings_hyphen_v5_hyphen_omni_hyphen_small/950200abde3a3bcf3d5bdfe5d28fb5bb5e7dfbb0/custom_st.py\", line 693, in _resolve_task\n raise ValueError(\n ...<3 lines>...\n )\nValueError: Task must be specified. Set it during loading (model_kwargs={'default_task': 'retrieval'}) or pass task='retrieval' to encode().\n", + "result": "FAIL(forward)", + "total_seconds": 24.917191720567644 + } + ] + }, + { + "index": 43, + "model": "Octen/Octen-Embedding-4B-INT8", + "revision": "7397789b62a36db1304f341ed04468d9f4d10a14", + "trending_rank": 43, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": "Quantized checkpoint requires a quantization backend outside this native floating-point Neuron sweep.", + "exclusion": "quantized", + "result": "EXCLUDED", + "status": "excluded", + "notes": "Quantized checkpoint requires a quantization backend outside this native floating-point Neuron sweep." + }, + { + "index": 44, + "model": "hotchpotch/bekko-embedding-v1-a8m", + "revision": "c721113d59a1d91b447450324f51c4b3332c924a", + "trending_rank": 44, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:40:12.311021+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 2.207026096060872, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.3013778626918793, + 0.6524449586868286, + 0.5371243357658386, + 0.5089138150215149 + ], + "cpu_seconds": 0.03168211691081524, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 46.82868221402168, + "neuron_scores": [ + 0.30137768387794495, + 0.65244460105896, + 0.5371241569519043, + 0.5089134573936462 + ], + "max_abs_error": 3.5762786865234375e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.04891674127429724, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 470, + "sample_interval_seconds": 0.1, + "peak_bytes": 564074105, + "peak_categories": { + "code": 7491048, + "tensors": 467668992, + "constants": 3866641, + "scratchpad": 67108864, + "misc": 13862784, + "dma_rings": 4075776 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 427598336, + "allocator_peak_reserved_bytes": 467664896, + "total_seconds": 68.98137910477817, + "prior_attempts": [] + }, + { + "index": 45, + "model": "KaLM-Embedding/KaLM-Reranker-V1-Nano-R2", + "revision": "48a5b221014ebb91f10400ffc7ef31f4960143ed", + "trending_rank": 45, + "downloads_rank": null, + "class": "CrossEncoder", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:40:14.849580+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 6.533512505702674, + "prompts": { + "retrieval": "Given a query, retrieve documents that answer the query." + }, + "parameter_dtypes": [ + "torch.float32" + ], + "cpu_scores": [ + 0.00414322828873992, + 0.9546420574188232, + 0.4421716332435608, + 0.6681984663009644 + ], + "cpu_seconds": 0.5679151052609086, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 136.0957063967362, + "neuron_scores": [ + 0.004143189173191786, + 0.9546418190002441, + 0.4421704411506653, + 0.6681967973709106 + ], + "max_abs_error": 1.6689300537109375e-06, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.21349625941365957, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 1365, + "sample_interval_seconds": 0.1, + "peak_bytes": 4118649897, + "peak_categories": { + "code": 16036400, + "tensors": 4001370112, + "constants": 5193785, + "scratchpad": 67108864, + "misc": 25401792, + "dma_rings": 3538944 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 3889145856, + "allocator_peak_reserved_bytes": 4001366016, + "total_seconds": 162.83513307757676, + "prior_attempts": [] + }, + { + "index": 46, + "model": "tencent/WeMM-Embedding-2B", + "revision": "bbd6cd4bf52cfc6716f752a2df80b2706720bd95", + "trending_rank": 46, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "reason": "Install model-declared qwen-vl-utils dependency before retry.", + "started_at": "2026-11-03T16:00:36.972096+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 7.381606991402805, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.46762001514434814, + 0.7261475920677185, + 0.6135473847389221, + 0.6402266025543213 + ], + "cpu_seconds": 1.7021749624982476, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 85.53720748145133, + "neuron_scores": [ + 0.4676196277141571, + 0.7261468768119812, + 0.6135469675064087, + 0.6402261257171631 + ], + "max_abs_error": 7.152557373046875e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.9560033204033971, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 876, + "sample_interval_seconds": 0.1, + "peak_bytes": 11108973537, + "peak_categories": { + "code": 15983184, + "tensors": 10974400512, + "constants": 8167441, + "scratchpad": 67108864, + "misc": 38678144, + "dma_rings": 4635392 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 10944451840, + "allocator_peak_reserved_bytes": 10974396416, + "total_seconds": 114.15666270814836, + "prior_attempts": [ + { + "index": 46, + "model": "tencent/WeMM-Embedding-2B", + "revision": "bbd6cd4bf52cfc6716f752a2df80b2706720bd95", + "trending_rank": 46, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:40:39.153633+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ImportError", + "error": "This modeling file requires the following packages that were not found in your environment: qwen_vl_utils. Run `pip install qwen_vl_utils`", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/046/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1346, in _load_config_modules\n module_class: type[Module] = self._load_module_class_from_ref(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n class_ref,\n ^^^^^^^^^^\n ...<6 lines>...\n local_files_only=local_files_only,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1599, in _load_module_class_from_ref\n return import_module_class(\n class_ref,\n ...<6 lines>...\n local_files_only=local_files_only,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/misc.py\", line 235, in import_module_class\n return get_class_from_dynamic_module(\n class_ref,\n ...<5 lines>...\n local_files_only=local_files_only,\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 614, in get_class_from_dynamic_module\n final_module = get_cached_module_file(\n repo_id,\n ...<7 lines>...\n repo_type=repo_type,\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 439, in get_cached_module_file\n modules_needed = check_imports(resolved_module_file)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 258, in check_imports\n raise ImportError(\n ...<2 lines>...\n )\nImportError: This modeling file requires the following packages that were not found in your environment: qwen_vl_utils. Run `pip install qwen_vl_utils`\n", + "result": "FAIL(load)", + "total_seconds": 25.148847079835832 + } + ] + }, + { + "index": 47, + "model": "tencent/WeMM-Embedding-9B", + "revision": "00c52839de57a6d4fd5b78cf5522ccf0ac8ea482", + "trending_rank": 47, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "bfloat16", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "reason": "Install model-declared qwen-vl-utils dependency before retry.", + "started_at": "2026-11-03T16:00:51.865696+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 9.836092847399414, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.bfloat16" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.4820074141025543, + 0.7529631853103638, + 0.580147922039032, + 0.5860584378242493 + ], + "cpu_seconds": 9.893546596169472, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 76.00104888062924, + "neuron_scores": [ + 0.48080533742904663, + 0.7537798285484314, + 0.5789978504180908, + 0.5852238535881042 + ], + "max_abs_error": 0.0012020766735076904, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 2.122203743085265, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 831, + "sample_interval_seconds": 0.1, + "peak_bytes": 19234354181, + "peak_categories": { + "code": 20984696, + "tensors": 19090378752, + "constants": 8036365, + "scratchpad": 67108864, + "misc": 42380160, + "dma_rings": 5465344 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 19042172224, + "allocator_peak_reserved_bytes": 19090374656, + "total_seconds": 127.3470405973494, + "prior_attempts": [ + { + "index": 47, + "model": "tencent/WeMM-Embedding-9B", + "revision": "00c52839de57a6d4fd5b78cf5522ccf0ac8ea482", + "trending_rank": 47, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "bfloat16", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:41:06.139170+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ImportError", + "error": "This modeling file requires the following packages that were not found in your environment: qwen_vl_utils. Run `pip install qwen_vl_utils`", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/047/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1346, in _load_config_modules\n module_class: type[Module] = self._load_module_class_from_ref(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n class_ref,\n ^^^^^^^^^^\n ...<6 lines>...\n local_files_only=local_files_only,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1599, in _load_module_class_from_ref\n return import_module_class(\n class_ref,\n ...<6 lines>...\n local_files_only=local_files_only,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/misc.py\", line 235, in import_module_class\n return get_class_from_dynamic_module(\n class_ref,\n ...<5 lines>...\n local_files_only=local_files_only,\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 614, in get_class_from_dynamic_module\n final_module = get_cached_module_file(\n repo_id,\n ...<7 lines>...\n repo_type=repo_type,\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 439, in get_cached_module_file\n modules_needed = check_imports(resolved_module_file)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 258, in check_imports\n raise ImportError(\n ...<2 lines>...\n )\nImportError: This modeling file requires the following packages that were not found in your environment: qwen_vl_utils. Run `pip install qwen_vl_utils`\n", + "result": "FAIL(load)", + "total_seconds": 13.699995523318648 + } + ] + }, + { + "index": 48, + "model": "Dibachain/Diba-Embed", + "revision": "9fe78de42f427081cce4a389177f9c1fea326dcf", + "trending_rank": 48, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:41:21.718370+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 2.7928918935358524, + "prompts": { + "query": "Instruct: Given a web search query, retrieve relevant passages that answer the query\nQuery:", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.4811299443244934, + 0.6901398301124573, + 0.5837672352790833, + 0.6643370985984802 + ], + "cpu_seconds": 0.5188999474048615, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 1.0025527849793434, + "neuron_scores": [ + 0.48112940788269043, + 0.6901392936706543, + 0.5837673544883728, + 0.6643365621566772 + ], + "max_abs_error": 5.364418029785156e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.2876144563779235, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 17, + "sample_interval_seconds": 0.1, + "peak_bytes": 2553584873, + "peak_categories": { + "code": 9742232, + "tensors": 2445283328, + "constants": 5668881, + "scratchpad": 67108864, + "misc": 21331776, + "dma_rings": 4449792 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 2390834944, + "allocator_peak_reserved_bytes": 2445279232, + "total_seconds": 26.23694735672325, + "prior_attempts": [] + }, + { + "index": 49, + "model": "kyr0/Winzling-Embed-a8m-64k", + "revision": "bfa8af8a8fbf3beb12a93a14d6f5b51875a36214", + "trending_rank": 49, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:41:23.706000+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.4712051330134273, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.3013778626918793, + 0.6654431223869324, + 0.5371243357658386, + 0.5089138150215149 + ], + "cpu_seconds": 0.030198005959391594, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 31.29920366499573, + "neuron_scores": [ + 0.30137768387794495, + 0.6654428243637085, + 0.5371241569519043, + 0.5089134573936462 + ], + "max_abs_error": 3.5762786865234375e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.029031899757683277, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 315, + "sample_interval_seconds": 0.1, + "peak_bytes": 269284033, + "peak_categories": { + "code": 7446000, + "tensors": 174067712, + "constants": 3866641, + "scratchpad": 67108864, + "misc": 13706176, + "dma_rings": 3088640 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 135706752, + "allocator_peak_reserved_bytes": 174063616, + "total_seconds": 53.8201359892264, + "prior_attempts": [] + }, + { + "index": 50, + "model": "Linkup-Platform/linkup-sparseup-embed-v1", + "revision": "08314498d4f6a3a205b930ab9f27001404ea94b8", + "trending_rank": 50, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": "SparseEncoder is outside this native Neuron text-retrieval sweep; sparse tensor output is unsupported.", + "exclusion": "sparse", + "result": "EXCLUDED", + "status": "excluded", + "notes": "SparseEncoder is outside this native Neuron text-retrieval sweep; sparse tensor output is unsupported." + }, + { + "index": 51, + "model": "RiverRider/motherlode-code-small-en-v0.1", + "revision": "10c3db34a27980cbca72227f736807aa8be487bb", + "trending_rank": 51, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:41:37.798950+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.415652096271515, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.44308722019195557, + 0.7941602468490601, + 0.7227752804756165, + 0.6388742923736572 + ], + "cpu_seconds": 0.06404289789497852, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 0.37342179473489523, + "neuron_scores": [ + 0.44308653473854065, + 0.7941591739654541, + 0.7227741479873657, + 0.638873279094696 + ], + "max_abs_error": 1.1324882507324219e-06, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.04909542668610811, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 6, + "sample_interval_seconds": 0.1, + "peak_bytes": 242218457, + "peak_categories": { + "code": 6303688, + "tensors": 153096192, + "constants": 3244049, + "scratchpad": 67108864, + "misc": 9624320, + "dma_rings": 2841344 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 144528768, + "allocator_peak_reserved_bytes": 153092096, + "total_seconds": 22.431978267617524, + "prior_attempts": [] + }, + { + "index": 52, + "model": "junaid008/hindko-embeddings", + "revision": "432690c2f36c31dfa9da8b58bfe763272f7614cb", + "trending_rank": 52, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:41:50.399512+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 5.426390751264989, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.43665847182273865, + 0.6403764486312866, + 0.5772411823272705, + 0.5291791558265686 + ], + "cpu_seconds": 0.2789019560441375, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 36.12070088274777, + "neuron_scores": [ + 0.43665796518325806, + 0.6403757333755493, + 0.5772407054901123, + 0.5291787981987 + ], + "max_abs_error": 7.152557373046875e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.06883412413299084, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 366, + "sample_interval_seconds": 0.1, + "peak_bytes": 2366933305, + "peak_categories": { + "code": 7671848, + "tensors": 2273316864, + "constants": 3833873, + "scratchpad": 67108864, + "misc": 12193280, + "dma_rings": 2808576 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 2246780928, + "allocator_peak_reserved_bytes": 2273312768, + "total_seconds": 74.4457817832008, + "prior_attempts": [] + }, + { + "index": 53, + "model": "lightonai/SlideOn", + "revision": "370c600e9886afc43ff8026695261e56ecfaa011", + "trending_rank": 53, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": "SparseEncoder is outside this native Neuron text-retrieval sweep; sparse tensor output is unsupported.", + "exclusion": "sparse", + "result": "EXCLUDED", + "status": "excluded", + "notes": "SparseEncoder is outside this native Neuron text-retrieval sweep; sparse tensor output is unsupported." + }, + { + "index": 54, + "model": "HukukcuApp/tr-legal-embedding-gemma-2", + "revision": "a33e497f3f123019d3b03fe40082992fffeac728", + "trending_rank": 54, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:42:02.918547+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "OSError", + "error": "Can't load feature extractor for 'HukukcuApp/tr-legal-embedding-gemma-2'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'HukukcuApp/tr-legal-embedding-gemma-2' is the correct path to a directory containing a preprocessor_config.json file", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/054/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 870, in __init__\n self.processor = AutoProcessor.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n tokenizer_name_or_path if tokenizer_name_or_path is not None else model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n **processor_kwargs,\n ^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/processing_auto.py\", line 350, in from_pretrained\n return processor_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, trust_remote_code=trust_remote_code, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/processing_utils.py\", line 1749, in from_pretrained\n args = cls._get_arguments_from_pretrained(pretrained_model_name_or_path, processor_dict, **kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/processing_utils.py\", line 1889, in _get_arguments_from_pretrained\n sub_processor = auto_processor_class.from_pretrained(\n pretrained_model_name_or_path, subfolder=subfolder, **kwargs\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/feature_extraction_auto.py\", line 329, in from_pretrained\n config_dict, _ = FeatureExtractionMixin.get_feature_extractor_dict(pretrained_model_name_or_path, **kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/feature_extraction_utils.py\", line 545, in get_feature_extractor_dict\n raise OSError(\n ...<4 lines>...\n )\nOSError: Can't load feature extractor for 'HukukcuApp/tr-legal-embedding-gemma-2'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'HukukcuApp/tr-legal-embedding-gemma-2' is the correct path to a directory containing a preprocessor_config.json file\n", + "result": "FAIL(load)", + "total_seconds": 14.706041608005762, + "prior_attempts": [] + }, + { + "index": 55, + "model": "abacusai/Smaug-AI-Image-Detector", + "revision": "c7c95951e04a87b884a4ad479401b1128c3903bd", + "trending_rank": 55, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": { + "vision_config": null, + "audio_config": null + }, + "excluded": "Classification task is outside the single-score text-retrieval example.", + "exclusion": "task", + "result": "EXCLUDED", + "status": "excluded", + "notes": "Classification task is outside the single-score text-retrieval example." + }, + { + "index": 56, + "model": "papr-ai/papr-embed-code-1-4b", + "revision": "2abaf9b8b8dbcda87259cbd274c75c40f085d8c7", + "trending_rank": 56, + 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the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ValueError", + "error": "MPNetModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/062/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 855, in __init__\n self.model = self._load_model(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2343, in _load_model\n return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 406, in from_pretrained\n return model_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4300, in from_pretrained\n model = cls(config, *model_args, **model_kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/mpnet/modeling_mpnet.py\", line 373, in __init__\n super().__init__(config)\n ~~~~~~~~~~~~~~~~^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1258, in __init__\n self.config._attn_implementation_internal = self._check_and_adjust_attn_implementation(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n self.config._attn_implementation,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<2 lines>...\n allow_all_kernels=hub_kernels.ALLOW_ALL_KERNELS,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1821, in _check_and_adjust_attn_implementation\n applicable_attn_implementation = self.get_correct_attn_implementation(\n applicable_attn_implementation, is_init_check\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1877, in get_correct_attn_implementation\n raise e\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1874, in get_correct_attn_implementation\n self._sdpa_can_dispatch(is_init_check)\n ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1665, in _sdpa_can_dispatch\n raise ValueError(\n ...<3 lines>...\n )\nValueError: MPNetModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`\n", + "result": "FAIL(load)", + "total_seconds": 10.56722302455455 + } + ] + }, + { + "index": 63, + "model": "sentence-transformers/clip-ViT-B-32-multilingual-v1", + "revision": "58edf8cada9e398793dca955574a48cbb7f18be2", + "trending_rank": 63, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:44:28.009909+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, 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"trending_rank": 68, + "downloads_rank": 21, + "class": "CrossEncoder", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:45:31.005467+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 2.707420035265386, + "prompts": {}, + "parameter_dtypes": [ + "torch.float32" + ], + "cpu_scores": [ + 0.8754974007606506, + 0.9981303811073303, + 0.9962502121925354, + 0.049137260764837265 + ], + "cpu_seconds": 2.6689382884651423, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 15.661622693762183, + "neuron_scores": [ + 0.8754978179931641, + 0.9981303215026855, + 0.9962501525878906, + 0.04913704842329025 + ], + "max_abs_error": 4.172325134277344e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.023638213984668255, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 163, + "sample_interval_seconds": 0.1, + "peak_bytes": 1260369981, + "peak_categories": { + "code": 5558256, + "tensors": 1178603520, + "constants": 1212429, + "scratchpad": 67108864, + "misc": 6411328, + "dma_rings": 1475584 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 1156753664, + "allocator_peak_reserved_bytes": 1178599424, + "total_seconds": 39.69002838805318, + "prior_attempts": [] + }, + { + "index": 69, + "model": "BAAI/bge-base-en-v1.5", + "revision": "a5beb1e3e68b9ab74eb54cfd186867f64f240e1a", + "trending_rank": 69, + "downloads_rank": 13, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:45:39.414554+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.1682966919615865, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.5682317018508911, + 0.8551056981086731, + 0.7346059679985046, + 0.696117103099823 + ], + "cpu_seconds": 0.12888348661363125, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 3.2500627348199487, + "neuron_scores": [ + 0.5682310461997986, + 0.8551044464111328, + 0.7346047163009644, + 0.6961159110069275 + ], + "max_abs_error": 1.2516975402832031e-06, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.04909901600331068, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 35, + "sample_interval_seconds": 0.1, + "peak_bytes": 590664905, + "peak_categories": { + "code": 6553336, + "tensors": 501223424, + "constants": 3375121, + "scratchpad": 67108864, + "misc": 9628352, + "dma_rings": 2775808 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 481544192, + "allocator_peak_reserved_bytes": 501219328, + "total_seconds": 23.074128158390522, + "prior_attempts": [] + }, + { + "index": 70, + "model": "jinaai/jina-embeddings-v2-base-en", + "revision": "322d4d7e2f35e84137961a65af894fda0385eb7a", + "trending_rank": 70, + "downloads_rank": 88, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:45:55.385742+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ModuleNotFoundError", + "error": "No module named 'transformers.onnx'", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/070/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 839, in __init__\n config, is_peft_model = self._load_config(model_name_or_path, backend, config_kwargs)\n ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2259, in _load_config\n return AutoConfig.from_pretrained(model_name_or_path, **config_kwargs), False\n ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/configuration_auto.py\", line 422, in from_pretrained\n config_class = get_class_from_dynamic_module(\n class_ref, pretrained_model_name_or_path, code_revision=code_revision, **kwargs\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 625, in get_class_from_dynamic_module\n return get_class_in_module(class_name, final_module, force_reload=force_download)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 309, in get_class_in_module\n module_spec.loader.exec_module(module)\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^\n File \"\", line 759, in exec_module\n File \"\", line 491, in _call_with_frames_removed\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_bert_hyphen_implementation/f3ec4cf7de7e561007f27c9efc7148b0bd713f81/configuration_bert.py\", line 22, in \n from transformers.onnx import OnnxConfig\nModuleNotFoundError: No module named 'transformers.onnx'\n", + "result": "FAIL(load)", + "total_seconds": 8.849647373892367, + "prior_attempts": [] + }, + { + "index": 71, + "model": "nomic-ai/nomic-embed-text-v1.5", + "revision": "e9b6763023c676ca8431644204f50c2b100d9aab", + "trending_rank": 71, + "downloads_rank": 8, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "reason": "Transformers 5.22 includes a native NomicBert implementation and checkpoint weight conversion; avoid legacy remote code using removed APIs.", + "started_at": "2026-11-03T16:01:54.928187+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 0.4089250825345516, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.6511314511299133, + 0.8881375789642334, + 0.7988847494125366, + 0.8139258027076721 + ], + "cpu_seconds": 0.13195148762315512, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 17.646083346568048, + "neuron_scores": [ + 0.6511314511299133, + 0.8881378769874573, + 0.7988849878311157, + 0.813926100730896 + ], + "max_abs_error": 2.980232238769531e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.08728538826107979, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 180, + "sample_interval_seconds": 0.1, + "peak_bytes": 728631449, + "peak_categories": { + "code": 7212552, + "tensors": 635441152, + "constants": 3440657, + "scratchpad": 67108864, + "misc": 12080000, + "dma_rings": 3348224 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 605238400, + "allocator_peak_reserved_bytes": 635437056, + "total_seconds": 44.2991419872269, + "prior_attempts": [ + { + "index": 71, + "model": "nomic-ai/nomic-embed-text-v1.5", + "revision": "e9b6763023c676ca8431644204f50c2b100d9aab", + "trending_rank": 71, + "downloads_rank": 8, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:46:04.380308+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 4.2537268456071615, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "status": "error", + "stage": "cpu_inference", + "error_type": "AttributeError", + "error": "'NomicBertModel' object has no attribute 'get_extended_attention_mask'", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/071/run.py\", line 63, in \n stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/071/run.py\", line 58, in score\n q=model.encode_query([query],batch_size=4,show_progress_bar=False,**kw)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 370, in encode_query\n return self.encode(\n ~~~~~~~~~~~^\n inputs=inputs,\n ^^^^^^^^^^^^^^\n ...<14 lines>...\n **kwargs,\n ^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 895, in encode\n all_embeddings = self._inference(inputs, device=device, **inference_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 963, in _inference\n out_features = self(features, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 600, in forward\n input = module(input, **module_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 1647, in forward\n model_output = model_method(**filtered_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/nomic_hyphen_ai/nomic_hyphen_bert_hyphen_2048/7710840340a098cfb869c4f65e87cf2b1b70caca/modeling_hf_nomic_bert.py\", line 1914, in forward\n attention_mask = self.get_extended_attention_mask(attention_mask, hidden_states.shape[:-1])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1972, in __getattr__\n raise AttributeError(\n f\"'{type(self).__name__}' object has no attribute '{name}'\"\n )\nAttributeError: 'NomicBertModel' object has no attribute 'get_extended_attention_mask'\n", + "result": "FAIL(forward)", + "total_seconds": 12.154953974299133 + } + ] + }, + { + "index": 72, + "model": "nasa-impact/nasa-smd-ibm-st-v2", + "revision": "e4a3e22048f0173ef150470cfbf67e9e8aaf4f8c", + "trending_rank": 72, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:46:05.769731+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.9315654337406158, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.5523449778556824, + 0.8154715299606323, + 0.5654679536819458, + 0.751962423324585 + ], + "cpu_seconds": 0.09866420552134514, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 34.718399844132364, + "neuron_scores": [ + 0.5523446202278137, + 0.8154709339141846, + 0.565467357635498, + 0.751961350440979 + ], + "max_abs_error": 1.0728836059570312e-06, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.04656910616904497, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 350, + "sample_interval_seconds": 0.1, + "peak_bytes": 656627857, + "peak_categories": { + "code": 7359360, + "tensors": 564137984, + "constants": 3571729, + "scratchpad": 67108864, + "misc": 11858176, + "dma_rings": 2591744 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 543998080, + "allocator_peak_reserved_bytes": 564133888, + "total_seconds": 51.54002279508859, + "prior_attempts": [] + }, + { + "index": 73, + "model": "Alibaba-NLP/gte-large-en-v1.5", + "revision": "104333d6af6f97649377c2afbde10a7704870c7b", + "trending_rank": 73, + "downloads_rank": 27, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:46:09.987170+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 3.194855031557381, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "status": "error", + "stage": "cpu_inference", + "error_type": "IndexError", + "error": "index 239254133933015924 is out of bounds for dimension 0 with size 11", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/073/run.py\", line 63, in \n stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/073/run.py\", line 58, in score\n q=model.encode_query([query],batch_size=4,show_progress_bar=False,**kw)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 370, in encode_query\n return self.encode(\n ~~~~~~~~~~~^\n inputs=inputs,\n ^^^^^^^^^^^^^^\n ...<14 lines>...\n **kwargs,\n ^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 895, in encode\n all_embeddings = self._inference(inputs, device=device, **inference_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 963, in _inference\n out_features = self(features, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 600, in forward\n input = module(input, **module_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 1647, in forward\n model_output = model_method(**filtered_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 901, in forward\n (embedding_output, attention_mask, rope_embeds, length) = self.embeddings(\n ~~~~~~~~~~~~~~~^\n unpad_inputs,\n ^^^^^^^^^^^^^\n ...<5 lines>...\n inputs_embeds=inputs_embeds\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 392, in forward\n rope_cos = rope_cos[position_ids].unsqueeze(2) # [bs, seq_len, 1, dim]\n ~~~~~~~~^^^^^^^^^^^^^^\nIndexError: index 239254133933015924 is out of bounds for dimension 0 with size 11\n", + "result": "FAIL(forward)", + "total_seconds": 11.818632579408586, + "prior_attempts": [] + }, + { + "index": 74, + "model": "udrearobert999/multi-qa-mpnet-base-cos-v1-contrastive-2e-1000samples", + "revision": "8a12b2b5886621830108824ffbb1382e66803888", + "trending_rank": 74, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "eager", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:46:24.205597+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.0450105546042323, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.8891924619674683, + 0.9820166230201721, + 0.9641423225402832, + 0.9801684021949768 + ], + "cpu_seconds": 0.13770453166216612, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 0.6448119217529893, + "neuron_scores": [ + 0.8891913294792175, + 0.9820157289505005, + 0.9641413688659668, + 0.9801676273345947 + ], + "max_abs_error": 1.1324882507324219e-06, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.07463741954416037, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 10, + "sample_interval_seconds": 0.1, + "peak_bytes": 604194325, + "peak_categories": { + "code": 9357832, + "tensors": 501223424, + "constants": 3833869, + "scratchpad": 67108864, + "misc": 18000128, + "dma_rings": 4670208 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 481360256, + "allocator_peak_reserved_bytes": 501219328, + "total_seconds": 21.715996171347797, + "prior_attempts": [ + { + "index": 74, + "model": "udrearobert999/multi-qa-mpnet-base-cos-v1-contrastive-2e-1000samples", + "revision": "8a12b2b5886621830108824ffbb1382e66803888", + "trending_rank": 74, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:46:12.772664+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ValueError", + "error": "MPNetModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/074/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 855, in __init__\n self.model = self._load_model(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2343, in _load_model\n return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 406, in from_pretrained\n return model_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4300, in from_pretrained\n model = cls(config, *model_args, **model_kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/mpnet/modeling_mpnet.py\", line 373, in __init__\n super().__init__(config)\n ~~~~~~~~~~~~~~~~^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1258, in __init__\n self.config._attn_implementation_internal = self._check_and_adjust_attn_implementation(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n self.config._attn_implementation,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<2 lines>...\n allow_all_kernels=hub_kernels.ALLOW_ALL_KERNELS,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1821, in _check_and_adjust_attn_implementation\n applicable_attn_implementation = self.get_correct_attn_implementation(\n applicable_attn_implementation, is_init_check\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1877, in get_correct_attn_implementation\n raise e\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1874, in get_correct_attn_implementation\n self._sdpa_can_dispatch(is_init_check)\n ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1665, in _sdpa_can_dispatch\n raise ValueError(\n ...<3 lines>...\n )\nValueError: MPNetModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`\n", + "result": "FAIL(load)", + "total_seconds": 10.028140273876488 + } + ] + }, + { + "index": 75, + "model": "nvidia/NV-Embed-v1", + "revision": "2e8b322e2b738a383dae0dde5fa19e0b28a5bb11", + "trending_rank": 75, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "bfloat16", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:46:17.899843+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "GatedRepoError", + "error": "403 Client Error. (Request ID: Root=1-6aea01d2-3206be3e053d1684092fc8e7;1a302a3a-37c9-46e0-94a8-99f64b2e4802)\n\nCannot access gated repo for url https://huggingface.co/nvidia/NV-Embed-v1/resolve/2e8b322e2b738a383dae0dde5fa19e0b28a5bb11/modules.json.\nAccess to model nvidia/NV-Embed-v1 is restricted and you are not in the authorized list. Visit https://huggingface.co/nvidia/NV-Embed-v1 to ask for access.", + "traceback": "httpx.HTTPStatusError: Client error '403 Forbidden' for url 'https://huggingface.co/nvidia/NV-Embed-v1/resolve/2e8b322e2b738a383dae0dde5fa19e0b28a5bb11/modules.json'\nFor more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/403\n\nThe above exception was the direct cause of the following exception:\n\nTraceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/075/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1190, in _load_modules\n modules_json_path = load_file_path(\n model_name_or_path,\n ...<4 lines>...\n local_files_only=local_files_only,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/file_io.py\", line 208, in load_file_path\n return hf_hub_download(\n model_name_or_path,\n ...<6 lines>...\n local_files_only=local_files_only,\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/utils/_validators.py\", line 89, in _inner_fn\n return fn(*args, **kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/utils/_http.py\", line 266, in _inner\n return fn(*args, **kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py\", line 1047, in hf_hub_download\n return _hf_hub_download_to_cache_dir(\n # Destination\n ...<15 lines>...\n dry_run=dry_run,\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py\", line 1194, in _hf_hub_download_to_cache_dir\n _raise_on_head_call_error(head_call_error, force_download, local_files_only)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/huggingface_hub/file_download.py\", line 1953, in _raise_on_head_call_error\n raise head_call_error\nhuggingface_hub.errors.GatedRepoError: 403 Client Error. (Request ID: Root=1-6aea01d2-3206be3e053d1684092fc8e7;1a302a3a-37c9-46e0-94a8-99f64b2e4802)\n\nCannot access gated repo for url https://huggingface.co/nvidia/NV-Embed-v1/resolve/2e8b322e2b738a383dae0dde5fa19e0b28a5bb11/modules.json.\nAccess to model nvidia/NV-Embed-v1 is restricted and you are not in the authorized list. Visit https://huggingface.co/nvidia/NV-Embed-v1 to ask for access.\n", + "result": "FAIL(load)", + "total_seconds": 8.890233975835145, + "prior_attempts": [] + }, + { + "index": 76, + "model": "deepvk/USER-base", + "revision": "e8446472f6024df155a04b2f0911b6044cabc51f", + "trending_rank": 76, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "eager", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:46:32.712895+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.5068676667287946, + "prompts": { + "query": "query: ", + "document": "", + "passage": "passage: " + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.377923846244812, + 0.6819409728050232, + 0.4981134235858917, + 0.5601119995117188 + ], + "cpu_seconds": 0.36737880390137434, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 44.95736795756966, + "neuron_scores": [ + 0.3779234290122986, + 0.6819397211074829, + 0.49811261892318726, + 0.5601109266281128 + ], + "max_abs_error": 1.2516975402832031e-06, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.10800229292362928, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 453, + "sample_interval_seconds": 0.1, + "peak_bytes": 669181880, + "peak_categories": { + "code": 7636408, + "tensors": 572526592, + "constants": 5373952, + "scratchpad": 67108864, + "misc": 13694464, + "dma_rings": 2841600 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 545769472, + "allocator_peak_reserved_bytes": 572522496, + "total_seconds": 63.34643253963441, + "prior_attempts": [ + { + "index": 76, + "model": "deepvk/USER-base", + "revision": "e8446472f6024df155a04b2f0911b6044cabc51f", + "trending_rank": 76, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:46:23.085938+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ValueError", + "error": "DebertaModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/076/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 855, in __init__\n self.model = self._load_model(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2343, in _load_model\n return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 406, in from_pretrained\n return model_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4300, in from_pretrained\n model = cls(config, *model_args, **model_kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/deberta/modeling_deberta.py\", line 629, in __init__\n super().__init__(config)\n ~~~~~~~~~~~~~~~~^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1258, in __init__\n self.config._attn_implementation_internal = self._check_and_adjust_attn_implementation(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n self.config._attn_implementation,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<2 lines>...\n allow_all_kernels=hub_kernels.ALLOW_ALL_KERNELS,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1821, in _check_and_adjust_attn_implementation\n applicable_attn_implementation = self.get_correct_attn_implementation(\n applicable_attn_implementation, is_init_check\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1877, in get_correct_attn_implementation\n raise e\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1874, in get_correct_attn_implementation\n self._sdpa_can_dispatch(is_init_check)\n ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1665, in _sdpa_can_dispatch\n raise ValueError(\n ...<3 lines>...\n )\nValueError: DebertaModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`\n", + "result": "FAIL(load)", + "total_seconds": 8.324606600217521 + } + ] + }, + { + "index": 77, + "model": "Jaume/gemma-2b-embeddings", + "revision": "86431f65d7c3f66b2af096c61e614a2958f191f1", + "trending_rank": 77, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:46:28.024988+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 4.274750509299338, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.9210729002952576, + 0.9032096862792969, + 0.9318515062332153, + 0.9134941101074219 + ], + "cpu_seconds": 6.217862844467163, + "cpu_top_document": 3, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 38.68630393128842, + "neuron_scores": [ + 0.921073317527771, + 0.9032103419303894, + 0.9318520426750183, + 0.9134945273399353 + ], + "max_abs_error": 6.556510925292969e-07, + "neuron_top_document": 3, + "mars_first": false, + "cpu_parity": true, + "neuron_repeat_seconds": 0.15275748260319233, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "FAIL(output)", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 410, + "sample_interval_seconds": 0.1, + "peak_bytes": 10209788025, + "peak_categories": { + "code": 11395752, + "tensors": 10108276736, + "constants": 4882449, + "scratchpad": 67108864, + "misc": 15922624, + "dma_rings": 2201600 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 10050966144, + "allocator_peak_reserved_bytes": 10108272640, + "total_seconds": 68.6340330131352, + "prior_attempts": [] + }, + { + "index": 78, + "model": "Alibaba-NLP/gte-multilingual-reranker-base", + "revision": "8215cf04918ba6f7b6a62bb44238ce2953d8831c", + "trending_rank": 78, + "downloads_rank": null, + "class": "CrossEncoder", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:46:48.108932+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 2.7446684883907437, + "prompts": {}, + "parameter_dtypes": [ + "torch.float32" + ], + "status": "error", + "stage": "cpu_inference", + "error_type": "IndexError", + "error": "index 139625091826798 is out of bounds for dimension 0 with size 32", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/078/run.py\", line 63, in \n stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/078/run.py\", line 55, in score\n values=model.predict([(query,d) for d in docs],batch_size=4,convert_to_tensor=True,show_progress_bar=False)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 209, in wrapper\n return func(self, *args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/cross_encoder/model.py\", line 645, in predict\n pred_scores = self._inference(inputs, device=device, **inference_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/cross_encoder/model.py\", line 689, in _inference\n out_features = self(features, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 600, in forward\n input = module(input, **module_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 1647, in forward\n model_output = model_method(**filtered_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 1117, in forward\n outputs = self.new(\n input_ids,\n ...<8 lines>...\n unpad_inputs=unpad_inputs,\n )\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 901, in forward\n (embedding_output, attention_mask, rope_embeds, length) = self.embeddings(\n ~~~~~~~~~~~~~~~^\n unpad_inputs,\n ^^^^^^^^^^^^^\n ...<5 lines>...\n inputs_embeds=inputs_embeds\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 392, in forward\n rope_cos = rope_cos[position_ids].unsqueeze(2) # [bs, seq_len, 1, dim]\n ~~~~~~~~^^^^^^^^^^^^^^\nIndexError: index 139625091826798 is out of bounds for dimension 0 with size 32\n", + "result": "FAIL(forward)", + "total_seconds": 15.83839768357575, + "prior_attempts": [] + }, + { + "index": 79, + "model": "akhooli/Arabic-SBERT-100K", + "revision": "67199ee95d81bb10047c946b1b4268c8703b83db", + "trending_rank": 79, + "downloads_rank": null, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:46:59.382279+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.3999376483261585, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.45112812519073486, + 0.5921509265899658, + 0.3681429922580719, + 0.6955137848854065 + ], + "cpu_seconds": 0.4114110991358757, + "cpu_top_document": 4, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 0.4038874404504895, + "neuron_scores": [ + 0.45112812519073486, + 0.5921508073806763, + 0.3681427240371704, + 0.6955137252807617 + ], + "max_abs_error": 2.682209014892578e-07, + "neuron_top_document": 4, + "mars_first": false, + "cpu_parity": true, + "neuron_repeat_seconds": 0.06409406755119562, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "FAIL(output)", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 7, + "sample_interval_seconds": 0.1, + "peak_bytes": 695672385, + "peak_categories": { + "code": 6654512, + "tensors": 606081024, + "constants": 3473425, + "scratchpad": 67108864, + "misc": 9832960, + "dma_rings": 2521600 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 587197440, + "allocator_peak_reserved_bytes": 606076928, + "total_seconds": 21.84079162403941, + "prior_attempts": [] + }, + { + "index": 80, + "model": "jinaai/jina-colbert-v2", + "revision": "a9dc5cd7293d4c71dbbba04829923ba4d0e4f6ea", + "trending_rank": 80, + "downloads_rank": null, + "class": "MultiVectorEncoder", + "dtype": "float32", + "attention": "eager", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:47:18.724653+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 5.669813772663474, + "prompts": { + "query": "[QueryMarker] ", + "document": "[DocumentMarker] " + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 17.971240997314453, + 21.52910804748535, + 20.408462524414062, + 20.498010635375977 + ], + "cpu_seconds": 0.44566130079329014, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 81.00222473405302, + "neuron_scores": [ + 17.97124671936035, + 21.529115676879883, + 20.408462524414062, + 20.498022079467773 + ], + "max_abs_error": 1.1444091796875e-05, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.16043350845575333, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 813, + "sample_interval_seconds": 0.1, + "peak_bytes": 2413350728, + "peak_categories": { + "code": 9888584, + "tensors": 2308968448, + "constants": 4335104, + "scratchpad": 67108864, + "misc": 19539200, + "dma_rings": 3510528 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 2248248256, + "allocator_peak_reserved_bytes": 2308964352, + "total_seconds": 102.76686627510935, + "prior_attempts": [ + { + "index": 80, + "model": "jinaai/jina-colbert-v2", + "revision": "a9dc5cd7293d4c71dbbba04829923ba4d0e4f6ea", + "trending_rank": 80, + "downloads_rank": null, + "class": "MultiVectorEncoder", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:47:06.055696+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ValueError", + "error": "XLMRobertaModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/080/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/multi_vector_encoder/model.py\", line 194, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1200, in _load_modules\n return self._load_default_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/multi_vector_encoder/model.py\", line 1340, in _load_default_modules\n transformer_model = Transformer(\n model_name_or_path,\n ...<7 lines>...\n **self._legacy.transformer_config,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 855, in __init__\n self.model = self._load_model(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2343, in _load_model\n return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 389, in from_pretrained\n return model_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/xlm_hyphen_roberta_hyphen_flash_hyphen_implementation/bd55a5ec8e6c0fb1d6c26efb4b6a4a74ce8a88d3/modeling_xlm_roberta.py\", line 442, in from_pretrained\n return super().from_pretrained(*args, **kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4300, in from_pretrained\n model = cls(config, *model_args, **model_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/xlm_hyphen_roberta_hyphen_flash_hyphen_implementation/bd55a5ec8e6c0fb1d6c26efb4b6a4a74ce8a88d3/modeling_xlm_roberta.py\", line 447, in __init__\n super().__init__(config)\n ~~~~~~~~~~~~~~~~^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1258, in __init__\n self.config._attn_implementation_internal = self._check_and_adjust_attn_implementation(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n self.config._attn_implementation,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<2 lines>...\n allow_all_kernels=hub_kernels.ALLOW_ALL_KERNELS,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1821, in _check_and_adjust_attn_implementation\n applicable_attn_implementation = self.get_correct_attn_implementation(\n applicable_attn_implementation, is_init_check\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1877, in get_correct_attn_implementation\n raise e\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1874, in get_correct_attn_implementation\n self._sdpa_can_dispatch(is_init_check)\n ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1665, in _sdpa_can_dispatch\n raise ValueError(\n ...<3 lines>...\n )\nValueError: XLMRobertaModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`\n", + "result": "FAIL(load)", + "total_seconds": 11.348125413060188 + } + ] + }, + { + "index": 81, + "model": "jinaai/jina-embeddings-v3", + "revision": "ab036b023d30b4d1138c4c3bfa9f0c445ab455d6", + "trending_rank": 81, + "downloads_rank": 32, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "eager", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:47:35.211638+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "AttributeError", + "error": "'XLMRobertaLoRA' object has no attribute 'all_tied_weights_keys'", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/081/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1404, in _load_config_modules\n module = module_class(model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_embeddings_hyphen_v3/ab036b023d30b4d1138c4c3bfa9f0c445ab455d6/custom_st.py\", line 87, in __init__\n self.auto_model = AutoModel.from_pretrained(model_name_or_path, config=self.config, **model_args)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 389, in from_pretrained\n return model_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/xlm_hyphen_roberta_hyphen_flash_hyphen_implementation/bd55a5ec8e6c0fb1d6c26efb4b6a4a74ce8a88d3/modeling_lora.py\", line 338, in from_pretrained\n return super().from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<9 lines>...\n **kwargs,\n ^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/xlm_hyphen_roberta_hyphen_flash_hyphen_implementation/bd55a5ec8e6c0fb1d6c26efb4b6a4a74ce8a88d3/modeling_xlm_roberta.py\", line 442, in from_pretrained\n return super().from_pretrained(*args, **kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4356, in from_pretrained\n loading_info = cls._finalize_model_loading(model, load_config, loading_info)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4524, in _finalize_model_loading\n model._move_missing_keys_from_meta_to_device(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n loading_info.missing_and_mismatched(),\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<2 lines>...\n load_config.hf_quantizer,\n ^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4781, in _move_missing_keys_from_meta_to_device\n for key in missing_keys - self.all_tied_weights_keys.keys():\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1972, in __getattr__\n raise AttributeError(\n f\"'{type(self).__name__}' object has no attribute '{name}'\"\n )\nAttributeError: 'XLMRobertaLoRA' object has no attribute 'all_tied_weights_keys'. Did you mean: '_tied_weights_keys'?\n", + "result": "FAIL(load)", + "total_seconds": 19.574221355840564, + "prior_attempts": [ + { + "index": 81, + "model": "jinaai/jina-embeddings-v3", + "revision": "ab036b023d30b4d1138c4c3bfa9f0c445ab455d6", + "trending_rank": 81, + "downloads_rank": 32, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:47:23.285436+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ValueError", + "error": "XLMRobertaLoRA does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/081/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1404, in _load_config_modules\n module = module_class(model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_embeddings_hyphen_v3/ab036b023d30b4d1138c4c3bfa9f0c445ab455d6/custom_st.py\", line 87, in __init__\n self.auto_model = AutoModel.from_pretrained(model_name_or_path, config=self.config, **model_args)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 389, in from_pretrained\n return model_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/xlm_hyphen_roberta_hyphen_flash_hyphen_implementation/bd55a5ec8e6c0fb1d6c26efb4b6a4a74ce8a88d3/modeling_lora.py\", line 338, in from_pretrained\n return super().from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<9 lines>...\n **kwargs,\n ^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/xlm_hyphen_roberta_hyphen_flash_hyphen_implementation/bd55a5ec8e6c0fb1d6c26efb4b6a4a74ce8a88d3/modeling_xlm_roberta.py\", line 442, in from_pretrained\n return super().from_pretrained(*args, **kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4300, in from_pretrained\n model = cls(config, *model_args, **model_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/xlm_hyphen_roberta_hyphen_flash_hyphen_implementation/bd55a5ec8e6c0fb1d6c26efb4b6a4a74ce8a88d3/modeling_lora.py\", line 254, in __init__\n super().__init__(config)\n ~~~~~~~~~~~~~~~~^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1258, in __init__\n self.config._attn_implementation_internal = self._check_and_adjust_attn_implementation(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n self.config._attn_implementation,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<2 lines>...\n allow_all_kernels=hub_kernels.ALLOW_ALL_KERNELS,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1821, in _check_and_adjust_attn_implementation\n applicable_attn_implementation = self.get_correct_attn_implementation(\n applicable_attn_implementation, is_init_check\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1877, in get_correct_attn_implementation\n raise e\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1874, in get_correct_attn_implementation\n self._sdpa_can_dispatch(is_init_check)\n ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1665, in _sdpa_can_dispatch\n raise ValueError(\n ...<3 lines>...\n )\nValueError: XLMRobertaLoRA does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`\n", + "result": "FAIL(load)", + "total_seconds": 10.663371765054762 + } + ] + }, + { + "index": 82, + "model": "dragonkue/bge-reranker-v2-m3-ko", + "revision": "2aca5884ecac490192af9ebd86836d9073d826cd", + "trending_rank": 82, + "downloads_rank": null, + "class": "CrossEncoder", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:47:37.878705+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 3.668647869490087, + "prompts": {}, + "parameter_dtypes": [ + "torch.float32" + ], + "cpu_scores": [ + 0.0076158237643539906, + 0.9999932050704956, + 0.964552640914917, + 0.9999319314956665 + ], + "cpu_seconds": 2.659851095639169, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 0.20474237203598022, + "neuron_scores": [ + 0.007615881972014904, + 0.9999931454658508, + 0.9645524621009827, + 0.9999318718910217 + ], + "max_abs_error": 1.7881393432617188e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.034791482612490654, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + 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"excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:52:03.168120+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ImportError", + "error": "cannot import name 'create_position_ids_from_input_ids' from 'transformers.models.xlm_roberta.modeling_xlm_roberta' (/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/xlm_roberta/modeling_xlm_roberta.py)", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/108/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 163, in wrapper\n return func(self, *args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/cross_encoder/model.py\", line 200, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1200, in _load_modules\n return self._load_default_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/cross_encoder/model.py\", line 337, in _load_default_modules\n transformer_model = Transformer(\n model_name_or_path,\n ...<5 lines>...\n backend=self.backend,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 855, in __init__\n self.model = self._load_model(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2343, in _load_model\n return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 381, in from_pretrained\n model_class = get_class_from_dynamic_module(\n class_ref, pretrained_model_name_or_path, code_revision=code_revision, **hub_kwargs, **kwargs\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 625, in get_class_from_dynamic_module\n return get_class_in_module(class_name, final_module, force_reload=force_download)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 309, in get_class_in_module\n module_spec.loader.exec_module(module)\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^\n File \"\", line 759, in exec_module\n File \"\", line 491, in _call_with_frames_removed\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_reranker_hyphen_v2_hyphen_base_hyphen_multilingual/9cfeff2df7d40d1b78e75e5e9cebec92a99813c9/modeling_xlm_roberta.py\", line 44, in \n from .embedding import XLMRobertaEmbeddings\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_reranker_hyphen_v2_hyphen_base_hyphen_multilingual/9cfeff2df7d40d1b78e75e5e9cebec92a99813c9/embedding.py\", line 11, in \n from transformers.models.xlm_roberta.modeling_xlm_roberta import create_position_ids_from_input_ids\nImportError: cannot import name 'create_position_ids_from_input_ids' from 'transformers.models.xlm_roberta.modeling_xlm_roberta' (/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/xlm_roberta/modeling_xlm_roberta.py)\n", + "result": "FAIL(load)", + "total_seconds": 10.194885298609734, + "prior_attempts": [] + }, + { + "index": 109, + "model": "thenlper/gte-small", + "revision": "17e1f347d17fe144873b1201da91788898c639cd", + "trending_rank": null, + "downloads_rank": 30, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:52:10.641559+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.0081146471202374, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.8394865393638611, + 0.930820882320404, + 0.9077175855636597, + 0.9031850099563599 + ], + "cpu_seconds": 0.0419626934453845, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 0.3552476419135928, + "neuron_scores": [ + 0.8394852876663208, + 0.9308195114135742, + 0.9077162742614746, + 0.9031835794448853 + ], + "max_abs_error": 1.430511474609375e-06, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.10197327472269535, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 6, + "sample_interval_seconds": 0.1, + "peak_bytes": 241230881, + "peak_categories": { + "code": 6359632, + "tensors": 153096192, + "constants": 3047441, + "scratchpad": 67108864, + "misc": 8984256, + "dma_rings": 2634496 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 144528896, + "allocator_peak_reserved_bytes": 153092096, + "total_seconds": 17.339452386833727, + "prior_attempts": [] + }, + { + "index": 110, + "model": "sentence-transformers/paraphrase-mpnet-base-v2", + "revision": "6cc9279c672dc57f94445ef259b28a1b736fec8f", + "trending_rank": null, + "downloads_rank": 31, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "eager", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:52:24.090416+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.0263016754761338, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.3722800314426422, + 0.7243042588233948, + 0.6553704738616943, + 0.5957000851631165 + ], + "cpu_seconds": 0.1333074662834406, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 0.5958021860569715, + "neuron_scores": [ + 0.3722800016403198, + 0.7243041396141052, + 0.6553703546524048, + 0.5957000255584717 + ], + "max_abs_error": 1.1920928955078125e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.0725036421790719, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 9, + "sample_interval_seconds": 0.1, + "peak_bytes": 604191253, + "peak_categories": { + "code": 9357832, + "tensors": 501223424, + "constants": 3833869, + "scratchpad": 67108864, + "misc": 18000128, + "dma_rings": 4667136 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 481360448, + "allocator_peak_reserved_bytes": 501219328, + "total_seconds": 19.92692092154175, + "prior_attempts": [ + { + "index": 110, + "model": "sentence-transformers/paraphrase-mpnet-base-v2", + "revision": "6cc9279c672dc57f94445ef259b28a1b736fec8f", + "trending_rank": null, + "downloads_rank": 31, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:52:15.158339+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ValueError", + "error": "MPNetModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/110/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 855, in __init__\n self.model = self._load_model(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2343, in _load_model\n return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 406, in from_pretrained\n return model_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4300, in from_pretrained\n model = cls(config, *model_args, **model_kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/mpnet/modeling_mpnet.py\", line 373, in __init__\n super().__init__(config)\n ~~~~~~~~~~~~~~~~^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1258, in __init__\n self.config._attn_implementation_internal = self._check_and_adjust_attn_implementation(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n self.config._attn_implementation,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<2 lines>...\n allow_all_kernels=hub_kernels.ALLOW_ALL_KERNELS,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1821, in _check_and_adjust_attn_implementation\n applicable_attn_implementation = self.get_correct_attn_implementation(\n applicable_attn_implementation, is_init_check\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1877, in get_correct_attn_implementation\n raise e\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1874, in get_correct_attn_implementation\n self._sdpa_can_dispatch(is_init_check)\n ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1665, in _sdpa_can_dispatch\n raise ValueError(\n ...<3 lines>...\n )\nValueError: MPNetModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`\n", + "result": "FAIL(load)", + "total_seconds": 7.7406725669279695 + } + ] + }, + { + "index": 111, + "model": "sentence-transformers/distiluse-base-multilingual-cased-v1", + "revision": "826fee3d516ebb14987355af373f5b69101c7006", + "trending_rank": null, + "downloads_rank": 33, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:52:25.127983+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.3539896085858345, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.41146302223205566, + 0.6181274056434631, + 0.6135995984077454, + 0.5464372634887695 + ], + "cpu_seconds": 0.2310029873624444, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 6.598759553395212, + "neuron_scores": [ + 0.41146308183670044, + 0.6181278824806213, + 0.6136000156402588, + 0.5464372634887695 + ], + "max_abs_error": 4.76837158203125e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.021002725698053837, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 69, + "sample_interval_seconds": 0.1, + "peak_bytes": 662522809, + "peak_categories": { + "code": 6500200, + "tensors": 574623744, + "constants": 3178513, + "scratchpad": 67108864, + "misc": 9204800, + "dma_rings": 1906688 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 564130048, + "allocator_peak_reserved_bytes": 574619648, + "total_seconds": 24.867785115726292, + "prior_attempts": [] + }, + { + "index": 112, + "model": "sentence-transformers/multi-qa-mpnet-base-dot-v1", + "revision": "17997f24dca0df1a4fed68894fb0e1e133e60482", + "trending_rank": null, + "downloads_rank": 34, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "eager", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:52:37.157163+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 0.9057708652690053, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 18.622793197631836, + 25.37649154663086, + 24.276288986206055, + 23.726768493652344 + ], + "cpu_seconds": 0.13503286056220531, + "cpu_top_document": 2, + "model_device": "neuron:0", + "status": "error", + "stage": "neuron_inference", + "error_type": "RuntimeError", + "error": "Inference tensors do not track version counter.", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/112/run.py\", line 69, in \n stage='neuron_inference';t=time.monotonic();actual=score();r['score_device']=str(actual.device)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/112/run.py\", line 61, in score\n values=model.similarity(q,d)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 1072, in similarity\n return self._similarity(embeddings1, embeddings2)\n ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/similarity.py\", line 115, in dot_score\n return torch.mm(a, b.transpose(0, 1)).to_dense()\n ~~~~~~~~~~~^^^^^^\nRuntimeError: Inference tensors do not track version counter.\n", + "result": "FAIL(forward)", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 9, + "sample_interval_seconds": 0.1, + "peak_bytes": 602256101, + "peak_categories": { + "code": 8931864, + "tensors": 501223424, + "constants": 3440653, + "scratchpad": 67108864, + "misc": 17067456, + "dma_rings": 4483840 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 481360448, + "allocator_peak_reserved_bytes": 501219328, + "total_seconds": 16.84018260613084, + "prior_attempts": [ + { + "index": 112, + "model": "sentence-transformers/multi-qa-mpnet-base-dot-v1", + "revision": "17997f24dca0df1a4fed68894fb0e1e133e60482", + "trending_rank": null, + "downloads_rank": 34, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:52:26.930147+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ValueError", + "error": "MPNetModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/112/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 855, in __init__\n self.model = self._load_model(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2343, in _load_model\n return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 406, in from_pretrained\n return model_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4300, in from_pretrained\n model = cls(config, *model_args, **model_kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/mpnet/modeling_mpnet.py\", line 373, in __init__\n super().__init__(config)\n ~~~~~~~~~~~~~~~~^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1258, in __init__\n self.config._attn_implementation_internal = self._check_and_adjust_attn_implementation(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n self.config._attn_implementation,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<2 lines>...\n allow_all_kernels=hub_kernels.ALLOW_ALL_KERNELS,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1821, in _check_and_adjust_attn_implementation\n applicable_attn_implementation = self.get_correct_attn_implementation(\n applicable_attn_implementation, is_init_check\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1877, in get_correct_attn_implementation\n raise e\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1874, in get_correct_attn_implementation\n self._sdpa_can_dispatch(is_init_check)\n ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1665, in _sdpa_can_dispatch\n raise ValueError(\n ...<3 lines>...\n )\nValueError: MPNetModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`\n", + "result": "FAIL(load)", + "total_seconds": 8.82788738142699 + } + ] + }, + { + "index": 113, + "model": "sentence-transformers/paraphrase-MiniLM-L6-v2", + "revision": "c9a2bfebc254878aee8c3aca9e6844d5bbb102d1", + "trending_rank": null, + "downloads_rank": 35, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:52:29.729330+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 0.8102488135918975, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.4128049910068512, + 0.6425286531448364, + 0.671911358833313, + 0.6263707876205444 + ], + "cpu_seconds": 0.053661770187318325, + "cpu_top_document": 3, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 0.3346906406804919, + "neuron_scores": [ + 0.4128049612045288, + 0.6425285339355469, + 0.671911358833313, + 0.6263706684112549 + ], + "max_abs_error": 1.1920928955078125e-07, + "neuron_top_document": 3, + "mars_first": false, + "cpu_parity": true, + "neuron_repeat_seconds": 0.03071187622845173, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "FAIL(output)", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 5, + "sample_interval_seconds": 0.1, + "peak_bytes": 224453665, + "peak_categories": { + "code": 6359632, + "tensors": 136318976, + "constants": 3047441, + "scratchpad": 67108864, + "misc": 8984256, + "dma_rings": 2634496 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 97223040, + "allocator_peak_reserved_bytes": 136314880, + "total_seconds": 16.178581200540066, + "prior_attempts": [] + }, + { + "index": 114, + "model": "jinaai/jina-embeddings-v2-small-en", + "revision": "44e7d1d6caec8c883c2d4b207588504d519788d0", + "trending_rank": null, + "downloads_rank": 38, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:52:45.768912+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ModuleNotFoundError", + "error": "No module named 'transformers.onnx'", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/114/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 839, in __init__\n config, is_peft_model = self._load_config(model_name_or_path, backend, config_kwargs)\n ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2259, in _load_config\n return AutoConfig.from_pretrained(model_name_or_path, **config_kwargs), False\n ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/configuration_auto.py\", line 422, in from_pretrained\n config_class = get_class_from_dynamic_module(\n class_ref, pretrained_model_name_or_path, code_revision=code_revision, **kwargs\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 625, in get_class_from_dynamic_module\n return get_class_in_module(class_name, final_module, force_reload=force_download)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/dynamic_module_utils.py\", line 309, in get_class_in_module\n module_spec.loader.exec_module(module)\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^\n File \"\", line 759, in exec_module\n File \"\", line 491, in _call_with_frames_removed\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_bert_hyphen_implementation/f3ec4cf7de7e561007f27c9efc7148b0bd713f81/configuration_bert.py\", line 22, in \n from transformers.onnx import OnnxConfig\nModuleNotFoundError: No module named 'transformers.onnx'\n", + "result": "FAIL(load)", + "total_seconds": 8.320869617164135, + "prior_attempts": [] + }, + { + "index": 115, + "model": "WhereIsAI/UAE-Large-V1", + "revision": "9c9b2c999b3350cfb3171ed429320668e39b00b8", + "trending_rank": null, + "downloads_rank": 41, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:52:47.677994+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 2.2766082268208265, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.5177715420722961, + 0.8304417133331299, + 0.6685433387756348, + 0.7035924196243286 + ], + "cpu_seconds": 0.3173334840685129, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 0.4041605442762375, + "neuron_scores": [ + 0.51777184009552, + 0.8304420709609985, + 0.6685433983802795, + 0.7035928964614868 + ], + "max_abs_error": 4.76837158203125e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.18421297706663609, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 9, + "sample_interval_seconds": 0.1, + "peak_bytes": 1461725137, + "peak_categories": { + "code": 6853184, + "tensors": 1371541504, + "constants": 3506193, + "scratchpad": 67108864, + "misc": 9797760, + "dma_rings": 2917632 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 1347096576, + "allocator_peak_reserved_bytes": 1371537408, + "total_seconds": 17.986716486513615, + "prior_attempts": [] + }, + { + "index": 116, + "model": "jhgan/ko-sroberta-multitask", + "revision": "8fca7c9c98c26599be0e14b9916b11a756a26f19", + "trending_rank": null, + "downloads_rank": 42, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:52:52.178170+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.2254862170666456, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.3725859224796295, + 0.5596363544464111, + 0.475629597902298, + 0.6078733205795288 + ], + "cpu_seconds": 0.2339512938633561, + "cpu_top_document": 4, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 46.99652501568198, + "neuron_scores": [ + 0.3725859224796295, + 0.5596362352371216, + 0.47562968730926514, + 0.6078732013702393 + ], + "max_abs_error": 1.1920928955078125e-07, + "neuron_top_document": 4, + "mars_first": false, + "cpu_parity": true, + "neuron_repeat_seconds": 0.04155152477324009, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "FAIL(output)", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 472, + "sample_interval_seconds": 0.1, + "peak_bytes": 604724833, + "peak_categories": { + "code": 7286160, + "tensors": 511709184, + "constants": 3866641, + "scratchpad": 67108864, + "misc": 12000704, + "dma_rings": 2753280 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 492647808, + "allocator_peak_reserved_bytes": 511705088, + "total_seconds": 62.91153274290264, + "prior_attempts": [] + }, + { + "index": 117, + "model": "cross-encoder/ms-marco-MiniLM-L12-v2", + "revision": "7b0235231ca2674cb8ca8f022859a6eba2b1c968", + "trending_rank": null, + "downloads_rank": 43, + "class": "CrossEncoder", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:52:55.549810+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 0.6701498832553625, + "prompts": {}, + "parameter_dtypes": [ + "torch.float32" + ], + "cpu_scores": [ + -7.184675693511963, + 9.501249313354492, + 5.721787929534912, + 6.84708309173584 + ], + "cpu_seconds": 0.06339482683688402, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 0.20195662882179022, + "neuron_scores": [ + -7.1846723556518555, + 9.50124740600586, + 5.721793174743652, + 6.847084999084473 + ], + "max_abs_error": 5.245208740234375e-06, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.03960189409554005, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 4, + "sample_interval_seconds": 0.1, + "peak_bytes": 235246949, + "peak_categories": { + "code": 5021656, + "tensors": 155193344, + "constants": 1212429, + "scratchpad": 67108864, + "misc": 5035136, + "dma_rings": 1675520 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 145319680, + "allocator_peak_reserved_bytes": 155189248, + "total_seconds": 16.558464873582125, + "prior_attempts": [] + }, + { + "index": 118, + "model": "intfloat/e5-small-v2", + "revision": "ffb93f3bd4047442299a41ebb6fa998a38507c52", + "trending_rank": null, + "downloads_rank": 44, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:52:56.003246+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 0.9329566936939955, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.8127754926681519, + 0.914289116859436, + 0.8680599331855774, + 0.8781478404998779 + ], + "cpu_seconds": 0.069936896674335, + "cpu_top_document": 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stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/123/run.py\", line 58, in score\n q=model.encode_query([query],batch_size=4,show_progress_bar=False,**kw)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 370, in encode_query\n return self.encode(\n ~~~~~~~~~~~^\n inputs=inputs,\n ^^^^^^^^^^^^^^\n ...<14 lines>...\n **kwargs,\n ^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 895, in encode\n all_embeddings = self._inference(inputs, device=device, **inference_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 963, in _inference\n out_features = self(features, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 600, in forward\n input = module(input, **module_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 1647, in forward\n model_output = model_method(**filtered_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 901, in forward\n (embedding_output, attention_mask, rope_embeds, length) = self.embeddings(\n ~~~~~~~~~~~~~~~^\n unpad_inputs,\n ^^^^^^^^^^^^^\n ...<5 lines>...\n inputs_embeds=inputs_embeds\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File 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"6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.0172114064916968, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.529904842376709, + 0.8319084048271179, + 0.6956507563591003, + 0.7484462261199951 + ], + "cpu_seconds": 0.1464661555364728, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 17.4146956698969, + "neuron_scores": [ + 0.5299039483070374, + 0.8319070935249329, + 0.6956503391265869, + 0.7484458684921265 + ], + "max_abs_error": 1.3113021850585938e-06, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.09378666989505291, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 177, + "sample_interval_seconds": 0.1, + "peak_bytes": 729432913, + "peak_categories": { + "code": 7402240, + "tensors": 635441152, + "constants": 3440657, + "scratchpad": 67108864, + "misc": 12566592, + "dma_rings": 3473408 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 604288256, + "allocator_peak_reserved_bytes": 635437056, + "total_seconds": 44.02619338501245, + "prior_attempts": [ + { + "index": 128, + "model": "nomic-ai/nomic-embed-text-v1", + "revision": "3ac47f125a41961d13b397d0332866be2f9152e1", + "trending_rank": null, + "downloads_rank": 57, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:54:14.669410+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 6.846553892828524, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "status": "error", + "stage": "cpu_inference", + "error_type": "AttributeError", + "error": "'NomicBertModel' object has no attribute 'get_extended_attention_mask'", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/128/run.py\", line 63, in \n stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/128/run.py\", line 58, in score\n q=model.encode_query([query],batch_size=4,show_progress_bar=False,**kw)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 370, in encode_query\n return self.encode(\n ~~~~~~~~~~~^\n inputs=inputs,\n ^^^^^^^^^^^^^^\n ...<14 lines>...\n **kwargs,\n ^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 895, in encode\n all_embeddings = self._inference(inputs, device=device, **inference_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 963, in _inference\n out_features = self(features, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 600, in forward\n input = module(input, **module_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 1647, in forward\n model_output = model_method(**filtered_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/nomic_hyphen_ai/nomic_hyphen_bert_hyphen_2048/7710840340a098cfb869c4f65e87cf2b1b70caca/modeling_hf_nomic_bert.py\", line 1914, in forward\n attention_mask = self.get_extended_attention_mask(attention_mask, hidden_states.shape[:-1])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1972, in __getattr__\n raise AttributeError(\n f\"'{type(self).__name__}' object has no attribute '{name}'\"\n )\nAttributeError: 'NomicBertModel' object has no attribute 'get_extended_attention_mask'\n", + "result": "FAIL(forward)", + "total_seconds": 18.67228259332478 + } + ] + }, + { + "index": 129, + "model": "nomic-ai/nomic-embed-text-v2-moe", + "revision": "1066b6599d099fbb93dfcb64f9c37a7c9e503e85", + "trending_rank": null, + "downloads_rank": 58, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:54:25.528812+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 6.00257970392704, + "prompts": { + "query": "search_query: ", + "document": "", + "passage": "search_document: ", + "Classification": "classification: ", + "MultilabelClassification": "classification: ", + "Clustering": "clustering: ", + "PairClassification": "classification: ", + "STS": "classification: ", + "Summarization": "classification: ", + "Speed": "search_document: " + }, + "parameter_dtypes": [ + "torch.float32" + ], + "status": "error", + "stage": "cpu_inference", + "error_type": "AttributeError", + "error": "'NomicBertModel' object has no attribute 'get_extended_attention_mask'", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/129/run.py\", line 63, in \n stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/129/run.py\", line 58, in score\n q=model.encode_query([query],batch_size=4,show_progress_bar=False,**kw)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 370, in encode_query\n return self.encode(\n ~~~~~~~~~~~^\n inputs=inputs,\n ^^^^^^^^^^^^^^\n ...<14 lines>...\n **kwargs,\n ^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 895, in encode\n all_embeddings = self._inference(inputs, device=device, **inference_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 963, in _inference\n out_features = self(features, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 600, in forward\n input = module(input, **module_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 1647, in forward\n model_output = model_method(**filtered_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/nomic_hyphen_ai/nomic_hyphen_bert_hyphen_2048/7710840340a098cfb869c4f65e87cf2b1b70caca/modeling_hf_nomic_bert.py\", line 1914, in forward\n attention_mask = self.get_extended_attention_mask(attention_mask, hidden_states.shape[:-1])\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1972, in __getattr__\n raise AttributeError(\n f\"'{type(self).__name__}' object has no attribute '{name}'\"\n )\nAttributeError: 'NomicBertModel' object has no attribute 'get_extended_attention_mask'\n", + "result": "FAIL(forward)", + "total_seconds": 13.943258575163782, + "prior_attempts": [] + }, + { + "index": 130, + "model": "intfloat/e5-large-v2", + "revision": "f169b11e22de13617baa190a028a32f3493550b6", + "trending_rank": null, + "downloads_rank": 59, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:54:26.252432+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 2.9802427757531404, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.7735358476638794, + 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"allocator_peak_allocated_bytes": 1347096576, + "allocator_peak_reserved_bytes": 1371537408, + "total_seconds": 23.081739421002567, + "prior_attempts": [] + }, + { + "index": 131, + "model": "sentence-transformers/paraphrase-MiniLM-L3-v2", + "revision": "4ca70771034acceecb2e72475f72050fcdde4ddc", + "trending_rank": null, + "downloads_rank": 60, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:54:28.694378+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 0.8898108704015613, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.42317527532577515, + 0.6578971147537231, + 0.6336928606033325, + 0.5873528718948364 + ], + "cpu_seconds": 0.04295923188328743, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 0.31014013569802046, + "neuron_scores": [ + 0.4231750965118408, + 0.6578975915908813, + 0.633692741394043, + 0.5873527526855469 + ], + "max_abs_error": 4.76837158203125e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.019109752029180527, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + 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+ ], + "max_abs_error": 2.980232238769531e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.09209704212844372, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 285, + "sample_interval_seconds": 0.1, + "peak_bytes": 469977272, + "peak_categories": { + "code": 6216568, + "tensors": 381685760, + "constants": 1572864, + "scratchpad": 67108864, + "misc": 10174784, + "dma_rings": 3218432 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 321292800, + "allocator_peak_reserved_bytes": 381681664, + "total_seconds": 46.715718819759786, + "prior_attempts": [ + { + "index": 132, + "model": "mixedbread-ai/mxbai-rerank-xsmall-v1", + "revision": "b5c6e9da73abc3711f593f705371cdbe9e0fe422", + "trending_rank": null, + "downloads_rank": 61, + "class": "CrossEncoder", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:54:34.766775+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ValueError", + "error": "DebertaV2ForSequenceClassification does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/132/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 163, in wrapper\n return func(self, *args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/cross_encoder/model.py\", line 200, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1200, in _load_modules\n return self._load_default_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/cross_encoder/model.py\", line 337, in _load_default_modules\n transformer_model = Transformer(\n model_name_or_path,\n ...<5 lines>...\n backend=self.backend,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 855, in __init__\n self.model = self._load_model(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2343, in _load_model\n return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 406, in from_pretrained\n return model_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4300, in from_pretrained\n model = cls(config, *model_args, **model_kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/deberta_v2/modeling_deberta_v2.py\", line 1002, in __init__\n super().__init__(config)\n ~~~~~~~~~~~~~~~~^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1258, in __init__\n self.config._attn_implementation_internal = self._check_and_adjust_attn_implementation(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n self.config._attn_implementation,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<2 lines>...\n allow_all_kernels=hub_kernels.ALLOW_ALL_KERNELS,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1821, in _check_and_adjust_attn_implementation\n applicable_attn_implementation = self.get_correct_attn_implementation(\n applicable_attn_implementation, is_init_check\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1877, in get_correct_attn_implementation\n raise e\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1874, in get_correct_attn_implementation\n self._sdpa_can_dispatch(is_init_check)\n ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1665, in _sdpa_can_dispatch\n raise ValueError(\n ...<3 lines>...\n )\nValueError: DebertaV2ForSequenceClassification does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`\n", + "result": "FAIL(load)", + "total_seconds": 10.315750057809055 + } + ] + }, + { + "index": 133, + "model": "sentence-transformers/multi-qa-MiniLM-L6-cos-v1", + "revision": "b207367332321f8e44f96e224ef15bc607f4dbf0", + "trending_rank": null, + "downloads_rank": 63, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:54:41.330529+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the 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false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:55:09.237654+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.3280827356502414, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 163.48626708984375, + 172.62042236328125, + 169.48434448242188, + 169.65316772460938 + ], + "cpu_seconds": 0.12728324253112078, + "cpu_top_document": 2, + "model_device": "neuron:0", + "status": "error", + "stage": "neuron_inference", + "error_type": "RuntimeError", + "error": "Inference tensors do not track version counter.", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/137/run.py\", line 69, in \n stage='neuron_inference';t=time.monotonic();actual=score();r['score_device']=str(actual.device)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/137/run.py\", line 61, in score\n values=model.similarity(q,d)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 1072, in similarity\n return self._similarity(embeddings1, embeddings2)\n ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/similarity.py\", line 115, in dot_score\n return torch.mm(a, b.transpose(0, 1)).to_dense()\n ~~~~~~~~~~~^^^^^^\nRuntimeError: Inference tensors do not track version counter.\n", + "result": "FAIL(forward)", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 6, + "sample_interval_seconds": 0.1, + "peak_bytes": 588585921, + "peak_categories": { + "code": 6350192, + "tensors": 501223424, + "constants": 2850833, + "scratchpad": 67108864, + "misc": 8545088, + "dma_rings": 2507520 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 481544320, + "allocator_peak_reserved_bytes": 501219328, + "total_seconds": 20.18780482839793, + "prior_attempts": [] + }, + { + "index": 138, + "model": "TencentBAC/Conan-embedding-v1", + "revision": "bb9749a57d4f02fd71722386f8d0f5a9398d7eeb", + "trending_rank": null, + "downloads_rank": 69, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:55:16.062527+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 2.4116813223809004, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.7179998159408569, + 0.8467733263969421, + 0.8121605515480042, + 0.7981007695198059 + ], + "cpu_seconds": 0.41972723323851824, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 34.923286225646734, + "neuron_scores": [ + 0.7179998159408569, + 0.8467733860015869, + 0.8121607899665833, + 0.7981007099151611 + ], + "max_abs_error": 2.384185791015625e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.28332080598920584, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 355, + "sample_interval_seconds": 0.1, + "peak_bytes": 1426998713, + "peak_categories": { + "code": 6976808, + "tensors": 1335889920, + "constants": 3702801, + "scratchpad": 67108864, + "misc": 10289024, + "dma_rings": 3031296 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 1316275712, + "allocator_peak_reserved_bytes": 1335885824, + "total_seconds": 55.9072351930663, + "prior_attempts": [] + }, + { + "index": 139, + "model": "cross-encoder/ms-marco-TinyBERT-L2-v2", + "revision": "81d1926f67cb8eee2c2be17ca9f793c7c3bd20cc", + "trending_rank": null, + "downloads_rank": 70, + "class": "CrossEncoder", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:55:31.237936+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 0.5549590475857258, + "prompts": {}, + "parameter_dtypes": [ + "torch.float32" + ], + "cpu_scores": [ + -10.877189636230469, + 6.952371597290039, + 5.873758316040039, + 5.699685573577881 + ], + "cpu_seconds": 0.015899132005870342, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 15.803866692818701, + "neuron_scores": [ + -10.877189636230469, + 6.952371120452881, + 5.873758792877197, + 5.699701309204102 + ], + "max_abs_error": 1.5735626220703125e-05, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.013494563288986683, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 160, + "sample_interval_seconds": 0.1, + "peak_bytes": 101190317, + "peak_categories": { + "code": 4951968, + "tensors": 20975616, + "constants": 1081357, + "scratchpad": 67108864, + "misc": 5387776, + "dma_rings": 1684736 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 19495680, + "allocator_peak_reserved_bytes": 20971520, + "total_seconds": 32.80624085199088, + "prior_attempts": [] + }, + { + "index": 140, + "model": "Alibaba-NLP/gte-base-en-v1.5", + "revision": "a829fd0e060bb84554da0dfd354d0de0f7712b7f", + "trending_rank": null, + "downloads_rank": 71, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:55:35.076933+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.5855842670425773, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "status": "error", + "stage": "cpu_inference", + "error_type": "IndexError", + "error": "index 140471200382993 is out of bounds for dimension 0 with size 11", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/140/run.py\", line 63, in \n stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n ~~~~~^^\n File \"/tmp/neuron-top100-sweep/runs/140/run.py\", line 58, in score\n q=model.encode_query([query],batch_size=4,show_progress_bar=False,**kw)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 370, in encode_query\n return self.encode(\n ~~~~~~~~~~~^\n inputs=inputs,\n ^^^^^^^^^^^^^^\n ...<14 lines>...\n **kwargs,\n ^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 895, in encode\n all_embeddings = self._inference(inputs, device=device, **inference_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/utils/_contextlib.py\", line 124, in decorate_context\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 963, in _inference\n out_features = self(features, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 600, in forward\n input = module(input, **module_kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 1647, in forward\n model_output = model_method(**filtered_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 901, in forward\n (embedding_output, attention_mask, rope_embeds, length) = self.embeddings(\n ~~~~~~~~~~~~~~~^\n unpad_inputs,\n ^^^^^^^^^^^^^\n ...<5 lines>...\n inputs_embeds=inputs_embeds\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1783, in _wrapped_call_impl\n return self._call_impl(*args, **kwargs)\n ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1794, in _call_impl\n return forward_call(*args, **kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/Alibaba_hyphen_NLP/new_hyphen_impl/40ced75c3017eb27626c9d4ea981bde21a2662f4/modeling.py\", line 392, in forward\n rope_cos = rope_cos[position_ids].unsqueeze(2) # [bs, seq_len, 1, dim]\n ~~~~~~~~^^^^^^^^^^^^^^\nIndexError: index 140471200382993 is out of bounds for dimension 0 with size 11\n", + "result": "FAIL(forward)", + "total_seconds": 12.225869985297322, + "prior_attempts": [] + }, + { + "index": 141, + "model": "emrecan/bert-base-turkish-cased-mean-nli-stsb-tr", + "revision": "7e10e2fbd7627fd0228eb2dbdc9e9da264442bbe", + "trending_rank": null, + "downloads_rank": 72, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:55:43.152000+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.2414588881656528, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.41886284947395325, + 0.5932007431983948, + 0.5092395544052124, + 0.5580816268920898 + ], + "cpu_seconds": 0.18779593240469694, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 30.580715341493487, + "neuron_scores": [ + 0.41886287927627563, + 0.5932007431983948, + 0.5092397928237915, + 0.558081865310669 + ], + "max_abs_error": 2.384185791015625e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.05917523521929979, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 308, + "sample_interval_seconds": 0.1, + "peak_bytes": 594374369, + "peak_categories": { + "code": 6549520, + "tensors": 505417728, + "constants": 3178513, + "scratchpad": 67108864, + "misc": 9491648, + "dma_rings": 2628096 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 486266880, + "allocator_peak_reserved_bytes": 505413632, + "total_seconds": 48.364770262502134, + "prior_attempts": [] + }, + { + "index": 142, + "model": "sentence-transformers/paraphrase-albert-small-v2", + "revision": "9d490b476eb5291c7885bb6d4961318740493cf2", + "trending_rank": null, + "downloads_rank": 73, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:55:49.012662+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 0.9063758421689272, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.36907443404197693, + 0.7583287954330444, + 0.6406499147415161, + 0.6637651324272156 + ], + "cpu_seconds": 0.049234882928431034, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 18.10002684034407, + "neuron_scores": [ + 0.3690744638442993, + 0.7583285570144653, + 0.6406497359275818, + 0.6637650728225708 + ], + "max_abs_error": 2.384185791015625e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.04195553809404373, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 183, + "sample_interval_seconds": 0.1, + "peak_bytes": 183646593, + "peak_categories": { + "code": 7375152, + "tensors": 88084480, + "constants": 4358161, + "scratchpad": 67108864, + "misc": 13182016, + "dma_rings": 3537920 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 58692352, + "allocator_peak_reserved_bytes": 88080384, + "total_seconds": 33.9962578965351, + "prior_attempts": [] + }, + { + "index": 143, + "model": "sentence-transformers/nli-mpnet-base-v2", + "revision": "c2f4dd9a1dc4337c28cfbd650433f761bb304c50", + "trending_rank": null, + "downloads_rank": 74, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "eager", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:56:16.084561+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.0226209675893188, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.2662433683872223, + 0.7299606204032898, + 0.6297932863235474, + 0.595600962638855 + ], + "cpu_seconds": 0.1311061130836606, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 0.6103363884612918, + "neuron_scores": [ + 0.2662433087825775, + 0.7299606800079346, + 0.6297934055328369, + 0.5956007838249207 + ], + "max_abs_error": 1.7881393432617188e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.07093656621873379, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 9, + "sample_interval_seconds": 0.1, + "peak_bytes": 604190229, + "peak_categories": { + "code": 9357832, + "tensors": 501223424, + "constants": 3833869, + "scratchpad": 67108864, + "misc": 18000128, + "dma_rings": 4666112 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 481097472, + "allocator_peak_reserved_bytes": 501219328, + "total_seconds": 21.752866292372346, + "prior_attempts": [ + { + "index": 143, + "model": "sentence-transformers/nli-mpnet-base-v2", + "revision": "c2f4dd9a1dc4337c28cfbd650433f761bb304c50", + "trending_rank": null, + "downloads_rank": 74, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:56:05.810425+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ValueError", + "error": "MPNetModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/143/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 855, in __init__\n self.model = self._load_model(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2343, in _load_model\n return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 406, in from_pretrained\n return model_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4300, in from_pretrained\n model = cls(config, *model_args, **model_kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/mpnet/modeling_mpnet.py\", line 373, in __init__\n super().__init__(config)\n ~~~~~~~~~~~~~~~~^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1258, in __init__\n self.config._attn_implementation_internal = self._check_and_adjust_attn_implementation(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n self.config._attn_implementation,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<2 lines>...\n allow_all_kernels=hub_kernels.ALLOW_ALL_KERNELS,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1821, in _check_and_adjust_attn_implementation\n applicable_attn_implementation = self.get_correct_attn_implementation(\n applicable_attn_implementation, is_init_check\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1877, in get_correct_attn_implementation\n raise e\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1874, in get_correct_attn_implementation\n self._sdpa_can_dispatch(is_init_check)\n ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1665, in _sdpa_can_dispatch\n raise ValueError(\n ...<3 lines>...\n )\nValueError: MPNetModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`\n", + "result": "FAIL(load)", + "total_seconds": 8.985691267997026 + } + ] + }, + { + "index": 144, + "model": "minishlab/potion-base-8M", + "revision": "bf8b056651a2c21b8d2565580b8569da283cab23", + "trending_rank": null, + "downloads_rank": 75, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:56:13.809543+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our 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"torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 3.60904539283365, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.4233960509300232, + 0.743354082107544, + 0.6508808135986328, + 0.6764653921127319 + ], + "cpu_seconds": 0.6333042802289128, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 0.4235305516049266, + "neuron_scores": [ + 0.4233955442905426, + 0.7433529496192932, + 0.6508801579475403, + 0.6764650344848633 + ], + "max_abs_error": 1.1324882507324219e-06, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.06527584232389927, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 13, + "sample_interval_seconds": 0.1, + "peak_bytes": 2435837305, + "peak_categories": { + "code": 7567400, + "tensors": 2342522880, + "constants": 3768337, + "scratchpad": 67108864, + "misc": 12039744, + "dma_rings": 2830080 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 2278391936, + "allocator_peak_reserved_bytes": 2342518784, + "total_seconds": 20.69017875008285, + "prior_attempts": [] + }, + { + "index": 153, + "model": "FremyCompany/BioLORD-2023", + "revision": "167aab527b238a50ca65224e6319215d2ff4fc9f", + "trending_rank": null, + "downloads_rank": 86, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "eager", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:57:13.282866+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 0.9831239739432931, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.4198802411556244, + 0.6363586783409119, + 0.5256239771842957, + 0.5443263649940491 + ], + "cpu_seconds": 0.12644123006612062, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 0.6738943727687001, + "neuron_scores": [ + 0.41988036036491394, + 0.636358916759491, + 0.52562415599823, + 0.5443264245986938 + ], + "max_abs_error": 2.384185791015625e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.07161634042859077, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 10, + "sample_interval_seconds": 0.1, + "peak_bytes": 606305813, + "peak_categories": { + "code": 9357832, + "tensors": 503320576, + "constants": 3833869, + "scratchpad": 67108864, + "misc": 18000128, + "dma_rings": 4684544 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 484243840, + "allocator_peak_reserved_bytes": 503316480, + "total_seconds": 18.67663632053882, + "prior_attempts": [ + { + "index": 153, + "model": "FremyCompany/BioLORD-2023", + "revision": "167aab527b238a50ca65224e6319215d2ff4fc9f", + "trending_rank": null, + "downloads_rank": 86, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:57:02.850822+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ValueError", + "error": "MPNetModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/153/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 855, in __init__\n self.model = self._load_model(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2343, in _load_model\n return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 406, in from_pretrained\n return model_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4300, in from_pretrained\n model = cls(config, *model_args, **model_kwargs)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/mpnet/modeling_mpnet.py\", line 373, in __init__\n super().__init__(config)\n ~~~~~~~~~~~~~~~~^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1258, in __init__\n self.config._attn_implementation_internal = self._check_and_adjust_attn_implementation(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n self.config._attn_implementation,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<2 lines>...\n allow_all_kernels=hub_kernels.ALLOW_ALL_KERNELS,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1821, in _check_and_adjust_attn_implementation\n applicable_attn_implementation = self.get_correct_attn_implementation(\n applicable_attn_implementation, is_init_check\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1877, in get_correct_attn_implementation\n raise e\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1874, in get_correct_attn_implementation\n self._sdpa_can_dispatch(is_init_check)\n ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1665, in _sdpa_can_dispatch\n raise ValueError(\n ...<3 lines>...\n )\nValueError: MPNetModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`\n", + "result": "FAIL(load)", + "total_seconds": 9.223272474482656 + } + ] + }, + { + "index": 154, + "model": "BAAI/bge-large-zh-v1.5", + "revision": "79e7739b6ab944e86d6171e44d24c997fc1e0116", + "trending_rank": null, + "downloads_rank": 89, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:57:14.593292+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 3.3294971622526646, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.46353769302368164, + 0.7270478010177612, + 0.6864646077156067, + 0.6734611988067627 + ], + "cpu_seconds": 7.744903035461903, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 9.977122595533729, + "neuron_scores": [ + 0.4635375142097473, + 0.7270478010177612, + 0.6864645481109619, + 0.6734611988067627 + ], + "max_abs_error": 1.7881393432617188e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.09579448495060205, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 104, + "sample_interval_seconds": 0.1, + "peak_bytes": 1425758105, + "peak_categories": { + "code": 6706248, + "tensors": 1335889920, + "constants": 3375121, + "scratchpad": 67108864, + "misc": 9798208, + "dma_rings": 2879744 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 1308924544, + "allocator_peak_reserved_bytes": 1335885824, + "total_seconds": 36.51802932564169, + "prior_attempts": [] + }, + { + "index": 155, + "model": "nomic-ai/nomic-embed-code", + "revision": "11114029805cee545ef111d5144b623787462a52", + "trending_rank": null, + "downloads_rank": 90, + "class": "SentenceTransformer", + "dtype": "bfloat16", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:58:49.567440+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.642259618267417, + "prompts": { + "query": "Represent this query for searching relevant code: ", + "document": "" + }, + "parameter_dtypes": [ + "torch.bfloat16" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.3248390257358551, + 0.6337037682533264, + 0.5248598456382751, + 0.5501180291175842 + ], + "cpu_seconds": 1.201702244579792, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 43.609398738481104, + "neuron_scores": [ + 0.3251861333847046, + 0.6337471604347229, + 0.5246393084526062, + 0.5499735474586487 + ], + "max_abs_error": 0.0003471076488494873, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.3450634339824319, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 457, + "sample_interval_seconds": 0.1, + "peak_bytes": 14433237173, + "peak_categories": { + "code": 14684456, + "tensors": 14321455104, + "constants": 3637261, + "scratchpad": 67108864, + "misc": 19381632, + "dma_rings": 6969856 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 14206526464, + "allocator_peak_reserved_bytes": 14321451008, + "total_seconds": 67.10503194388002, + "prior_attempts": [ + { + "index": 155, + "model": "nomic-ai/nomic-embed-code", + "revision": "11114029805cee545ef111d5144b623787462a52", + "trending_rank": null, + "downloads_rank": 90, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:57:15.844344+00:00", + "physical_visible_core": "4", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 7.0312007162719965, + "prompts": { + "query": "Represent this query for searching relevant code: ", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "cpu", + "cpu" + ], + "cpu_scores": [ + 0.3257618844509125, + 0.634091317653656, + 0.5247002243995667, + 0.550145149230957 + ], + "cpu_seconds": 53.59399434737861, + "cpu_top_document": 2, + "status": "error", + "stage": "move_to_neuron", + "error_type": "RuntimeError", + "error": "NRT Execution error occurred on Neuron for operation=neuron::alloc::lazy\nerror message=\"NRT EXECUTION FAILED: lazy::AllocBind: NRT_RESOURCE; no pending ops on stream to wait for (cannot defer), Failed to allocate resource\"\nNote: Neuron errors are reported asynchronously. The Python traceback shows where the\nerror was detected (synchronization point), not necessarily where the failing operation\nwas dispatched. For synchronous error reporting, set NEURON_LAUNCH_BLOCKING=1.", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/155/run.py\", line 67, in \n stage='move_to_neuron';torch.neuron.init();memory_monitor=DeviceMemoryMonitor();memory_monitor.start();model.to('neuron:0');r['model_device']=str(model.device)\n ~~~~~~~~^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1720, in to\n result = super().to(*args, **kwargs)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1388, in to\n return self._apply(convert)\n ~~~~~~~~~~~^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1748, in _apply\n return super()._apply(*args, **kwargs)\n ~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 933, in _apply\n module._apply(fn)\n ~~~~~~~~~~~~~^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 933, in _apply\n module._apply(fn)\n ~~~~~~~~~~~~~^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 933, in _apply\n module._apply(fn)\n ~~~~~~~~~~~~~^^^^\n [Previous line repeated 3 more times]\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 966, in _apply\n param_applied = fn(param)\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1374, in convert\n return t.to(\n ~~~~^\n device,\n ^^^^^^^\n dtype if t.is_floating_point() or t.is_complex() else None,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n non_blocking,\n ^^^^^^^^^^^^^\n )\n ^\nRuntimeError: NRT Execution error occurred on Neuron for operation=neuron::alloc::lazy\nerror message=\"NRT EXECUTION FAILED: lazy::AllocBind: NRT_RESOURCE; no pending ops on stream to wait for (cannot defer), Failed to allocate resource\"\nNote: Neuron errors are reported asynchronously. The Python traceback shows where the\nerror was detected (synchronization point), not necessarily where the failing operation\nwas dispatched. For synchronous error reporting, set NEURON_LAUNCH_BLOCKING=1.\n", + "result": "FAIL(load)", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 126, + "sample_interval_seconds": 0.1, + "peak_bytes": 25351328528, + "peak_categories": { + "code": 3880080, + "tensors": 25346179072, + "misc": 1207936, + "dma_rings": 61440 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 25214158848, + "allocator_peak_reserved_bytes": 25346179072, + "total_seconds": 91.20005322620273 + } + ] + }, + { + "index": 156, + "model": "nvidia/llama-nemotron-embed-1b-v2", + "revision": "113abe4acafa848e77ead9c0623205e511932348", + "trending_rank": null, + "downloads_rank": 91, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:57:22.463211+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 5.778271097689867, + "prompts": { + "query": "query: ", + "document": "passage: " + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.2428959161043167, + 0.617745041847229, + 0.40710389614105225, + 0.502673864364624 + ], + "cpu_seconds": 0.9158972855657339, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 43.349398490041494, + "neuron_scores": [ + 0.24289590120315552, + 0.617744505405426, + 0.40710338950157166, + 0.5026735663414001 + ], + "max_abs_error": 5.364418029785156e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.11499457247555256, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 440, + "sample_interval_seconds": 0.1, + "peak_bytes": 5122843873, + "peak_categories": { + "code": 9823056, + "tensors": 5022683136, + "constants": 4751377, + "scratchpad": 67108864, + "misc": 16075136, + "dma_rings": 2402304 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 4962157184, + "allocator_peak_reserved_bytes": 5022679040, + "total_seconds": 94.59216973185539, + "prior_attempts": [] + }, + { + "index": 157, + "model": "nvidia/Nemotron-3-Embed-1B-BF16", + "revision": "c0c9fea93ea424587517f2c59e20db9f1d6bf615", + "trending_rank": null, + "downloads_rank": 92, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:57:34.144062+00:00", + "physical_visible_core": "12", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 6.593185469508171, + "prompts": { + "query": "query: ", + "document": "passage: " + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.24806897342205048, + 0.6449322700500488, + 0.4405224919319153, + 0.4167785048484802 + ], + "cpu_seconds": 0.7247543530538678, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 48.09893609303981, + "neuron_scores": [ + 0.24806880950927734, + 0.6449317932128906, + 0.4405222237110138, + 0.4167780876159668 + ], + "max_abs_error": 4.76837158203125e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.13140135258436203, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 488, + "sample_interval_seconds": 0.1, + "peak_bytes": 4703284729, + "peak_categories": { + "code": 10241576, + "tensors": 4599058432, + "constants": 5275665, + "scratchpad": 67108864, + "misc": 18638016, + "dma_rings": 2962176 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 4577604864, + "allocator_peak_reserved_bytes": 4599054336, + "total_seconds": 88.08173035178334, + "prior_attempts": [] + }, + { + "index": 158, + "model": "nvidia/NV-Embed-v2", + "revision": "3fa59658547db50a1e8e3346cf057fd0c77ed6ef", + "trending_rank": null, + "downloads_rank": 93, + "class": "SentenceTransformer", + "dtype": "bfloat16", + "attention": "eager", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:58:12.973659+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "AttributeError", + "error": "'NVEmbedModel' object has no attribute 'all_tied_weights_keys'", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/158/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 855, in __init__\n self.model = self._load_model(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2343, in _load_model\n return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 389, in from_pretrained\n return model_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4356, in from_pretrained\n loading_info = cls._finalize_model_loading(model, load_config, loading_info)\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4524, in _finalize_model_loading\n model._move_missing_keys_from_meta_to_device(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n loading_info.missing_and_mismatched(),\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<2 lines>...\n load_config.hf_quantizer,\n ^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4781, in _move_missing_keys_from_meta_to_device\n for key in missing_keys - self.all_tied_weights_keys.keys():\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/.venv-oct09/lib/python3.14/site-packages/torch/nn/modules/module.py\", line 1972, in __getattr__\n raise AttributeError(\n f\"'{type(self).__name__}' object has no attribute '{name}'\"\n )\nAttributeError: 'NVEmbedModel' object has no attribute 'all_tied_weights_keys'. Did you mean: '_tied_weights_keys'?\n", + "result": "FAIL(load)", + "total_seconds": 29.60385298728943, + "prior_attempts": [ + { + "index": 158, + "model": "nvidia/NV-Embed-v2", + "revision": "3fa59658547db50a1e8e3346cf057fd0c77ed6ef", + "trending_rank": null, + "downloads_rank": 93, + "class": "SentenceTransformer", + "dtype": "bfloat16", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:57:53.087442+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "status": "error", + "stage": "load_cpu", + "error_type": "ValueError", + "error": "NVEmbedModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`", + "traceback": "Traceback (most recent call last):\n File \"/tmp/neuron-top100-sweep/runs/158/run.py\", line 50, in \n model=cls(SPEC['model'],revision=SPEC['revision'],device='cpu',trust_remote_code=SPEC['trust_remote_code'],config_kwargs=SPEC['config_kwargs'],model_kwargs={'torch_dtype':dtype,'attn_implementation':SPEC['attention']})\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 46, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/sentence_transformer/model.py\", line 193, in __init__\n super().__init__(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path=model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<13 lines>...\n default_prompt_name=default_prompt_name,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 256, in __init__\n modules, self.module_kwargs = self._load_modules(\n ~~~~~~~~~~~~~~~~~~^\n model_name_or_path,\n ^^^^^^^^^^^^^^^^^^^\n ...<7 lines>...\n config_kwargs=config_kwargs,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1211, in _load_modules\n return self._load_config_modules(model_name_or_path, **load_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py\", line 1431, in _load_config_modules\n module = module_class.load(\n model_name_or_path,\n ...<12 lines>...\n **extra_load_kwargs,\n )\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2641, in load\n return cls(model_name_or_path=model_name_or_path, **init_kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/util/decorators.py\", line 92, in wrapper\n return func(*args, **kwargs)\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 855, in __init__\n self.model = self._load_model(\n ~~~~~~~~~~~~~~~~^\n model_name_or_path, transformer_task, config, backend, is_peft_model, **model_kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/home/jingyahuang/sentence-transformers/sentence_transformers/base/modules/transformer.py\", line 2343, in _load_model\n return model_cls.from_pretrained(model_name_or_path, config=config, **model_kwargs)\n ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/auto/auto_factory.py\", line 389, in from_pretrained\n return model_class.from_pretrained(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 4300, in from_pretrained\n model = cls(config, *model_args, **model_kwargs)\n File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/nvidia/NV_hyphen_Embed_hyphen_v2/3fa59658547db50a1e8e3346cf057fd0c77ed6ef/modeling_nvembed.py\", line 320, in __init__\n super().__init__(config)\n ~~~~~~~~~~~~~~~~^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1258, in __init__\n self.config._attn_implementation_internal = self._check_and_adjust_attn_implementation(\n ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^\n self.config._attn_implementation,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n ...<2 lines>...\n allow_all_kernels=hub_kernels.ALLOW_ALL_KERNELS,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n )\n ^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1821, in _check_and_adjust_attn_implementation\n applicable_attn_implementation = self.get_correct_attn_implementation(\n applicable_attn_implementation, is_init_check\n )\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1877, in get_correct_attn_implementation\n raise e\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1874, in get_correct_attn_implementation\n self._sdpa_can_dispatch(is_init_check)\n ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^\n File \"/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/modeling_utils.py\", line 1665, in _sdpa_can_dispatch\n raise ValueError(\n ...<3 lines>...\n )\nValueError: NVEmbedModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation=\"eager\"` meanwhile. Example: `model = AutoModel.from_pretrained(\"openai/whisper-tiny\", attn_implementation=\"eager\")`\n", + "result": "FAIL(load)", + "total_seconds": 18.42478364240378 + } + ] + }, + { + "index": 159, + "model": "sentence-transformers/bert-base-nli-mean-tokens", + "revision": "160a52b38a51ae87295ec3eabcf11755e5d27a8d", + "trending_rank": null, + "downloads_rank": 94, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": false, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:58:43.865277+00:00", + "physical_visible_core": "0", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 1.6803692784160376, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.398617148399353, + 0.8333069682121277, + 0.7272908687591553, + 0.7329380512237549 + ], + "cpu_seconds": 0.13391133304685354, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 0.37846680358052254, + "neuron_scores": [ + 0.3986172378063202, + 0.833306074142456, + 0.7272908091545105, + 0.7329383492469788 + ], + "max_abs_error": 8.940696716308594e-07, + "neuron_top_document": 2, + "mars_first": true, + "cpu_parity": true, + "neuron_repeat_seconds": 0.051052977330982685, + "repeat_max_abs_error": 0.0, + "repeat_stable": true, + "status": "executed", + "result": "PASS", + "memory_monitor": { + "method": "Neuron runtime HBM usage breakdown sampled every 100 ms", + "sample_count": 7, + "sample_interval_seconds": 0.1, + "peak_bytes": 590471889, + "peak_categories": { + "code": 6627840, + "tensors": 501223424, + "constants": 3309585, + "scratchpad": 67108864, + "misc": 9489856, + "dma_rings": 2712320 + }, + "capacity_bytes": 25769803776 + }, + "allocator_peak_allocated_bytes": 481544320, + "allocator_peak_reserved_bytes": 501219328, + "total_seconds": 26.488013215363026, + "prior_attempts": [] + }, + { + "index": 160, + "model": "perplexity-ai/pplx-embed-v1-0.6b", + "revision": "2c4d510dd4a732063c31a0f70193e35067b51fd8", + "trending_rank": null, + "downloads_rank": 95, + "class": "SentenceTransformer", + "dtype": "float32", + "attention": "sdpa", + "trust_remote_code": true, + "config_kwargs": {}, + "excluded": null, + "exclusion": null, + "started_at": "2026-11-03T15:58:59.197488+00:00", + "physical_visible_core": "8", + "torch": "2.14.0+cpu", + "transformers": "5.22.1", + "sentence_transformers": "6.3.0.dev0", + "python": "3.14.4", + "query": "Which planet is known as the Red Planet?", + "documents": [ + "Venus is often called Earth's twin because of its similar size and proximity.", + "Mars, known for its reddish appearance, is often referred to as the Red Planet.", + "Jupiter, the largest planet in our solar system, has a prominent red spot.", + "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." + ], + "batch_size": 4, + "load_seconds": 3.4710025703534484, + "prompts": { + "query": "", + "document": "" + }, + "parameter_dtypes": [ + "torch.float32" + ], + "embedding_devices": [ + "neuron:0", + "neuron:0" + ], + "cpu_scores": [ + 0.36221835017204285, + 0.7826368808746338, + 0.5675452351570129, + 0.6321296691894531 + ], + "cpu_seconds": 0.5104384804144502, + "cpu_top_document": 2, + "model_device": "neuron:0", + "score_device": "neuron:0", + "neuron_first_seconds": 45.28033387474716, + 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