Rerun all failed Sentence Transformers checkpoints after access updates

README.md

@@ -123,6 +123,18 @@ Downloads views use the live Hub ordering, which can change after this snapshot.
 | Downloads | 80 | 6 | 12 | 2 | 100 |
 | Unique models | 119 | 15 | 18 | 12 | 164 |
 
+All 33 failed checkpoints were rerun after access was granted to the two gated
+repositories. Their outcome categories are unchanged, but the current errors and
+measurements are from these fresh runs. `litert-community/embeddinggemma-300m`
+contains TFLite exports rather than a native Transformers checkpoint and fails
+model loading; `google/embeddinggemma-300m` already passes. `nvidia/NV-Embed-v1`
+now reaches its required custom code (`trust_remote_code=True`), which imports
+`MISTRAL_INPUTS_DOCSTRING`, unavailable in the tested Transformers 5.22.1 stack.
+Neither current failure is an access error. The comparison is recorded in
+`validation/sentence-transformers/2026-11-03-top100/failed-rerun-1.json`;
+previous scripts, logs, results, and captured memory samples are preserved under
+`prior_runs/failed-rerun-1/` in the same directory.
+
 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
@@ -144,7 +156,7 @@ CPU score agreement at the same precision (`atol=rtol=0.001`), and a stable repe
 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
+CPU-side incompatibilities, unsupported checkpoint formats, 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.

data/trn2/neuronxcc-2.28.4568.0+0163fa9e/sentence-transformers-6.3.0.dev0.parquet

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-size 165506
+oid sha256:cfa069ce6fb04d18c4758dae01829bc5bdf2ab122fbf0b50323004a4b9659931
+size 164325

validation/sentence-transformers/2026-11-03-top100/failed-rerun-1.json

@@ -0,0 +1,407 @@
+{
+  "count": 33,
+  "results": {
+    "FAIL(output)": 15,
+    "FAIL(load)": 9,
+    "FAIL(forward)": 9
+  },
+  "source_commit": "6be0abf38d00d70bb3c732131df59ad073ff3768",
+  "reruns": [
+    {
+      "model": "nvidia/Nemotron-3.5-Rerank-8B-BF16",
+      "index": 7,
+      "previous_result": "FAIL(output)",
+      "result": "FAIL(output)",
+      "previous_started_at": "2026-11-03T15:28:39.934071+00:00",
+      "started_at": "2026-11-03T16:26:48.318127+00:00",
+      "previous_stage": null,
+      "stage": null,
+      "previous_error": null,
+      "error": null
+    },
+    {
+      "model": "Omartificial-Intelligence-Space/Arabic-Triplet-Matryoshka-V2",
+      "index": 21,
+      "previous_result": "FAIL(output)",
+      "result": "FAIL(output)",
+      "previous_started_at": "2026-11-03T15:31:28.531464+00:00",
+      "started_at": "2026-11-03T16:26:48.318264+00:00",
+      "previous_stage": null,
+      "stage": null,
+      "previous_error": null,
+      "error": null
+    },
+    {
+      "model": "litert-community/embeddinggemma-300m",
+      "index": 23,
+      "previous_result": "FAIL(load)",
+      "result": "FAIL(load)",
+      "previous_started_at": "2026-11-03T15:31:58.747378+00:00",
+      "started_at": "2026-11-03T16:26:48.324742+00:00",
+      "previous_stage": "load_cpu",
+      "stage": "load_cpu",
+      "previous_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.",
+      "error": "Unrecognized model in litert-community/embeddinggemma-300m. Should have a `model_type` key in its config.json."
+    },
+    {
+      "model": "Qwen/Qwen3-VL-Embedding-8B",
+      "index": 24,
+      "previous_result": "FAIL(output)",
+      "result": "FAIL(output)",
+      "previous_started_at": "2026-11-03T15:32:09.263638+00:00",
+      "started_at": "2026-11-03T16:26:48.323954+00:00",
+      "previous_stage": null,
+      "stage": null,
+      "previous_error": null,
+      "error": null
+    },
+    {
+      "model": "BrunoHays/embeddinggemma-2-nullspace-audio",
+      "index": 29,
+      "previous_result": "FAIL(load)",
+      "result": "FAIL(load)",
+      "previous_started_at": "2026-11-03T15:34:11.569070+00:00",
+      "started_at": "2026-11-03T16:27:22.235996+00:00",
+      "previous_stage": "load_cpu",
+      "stage": "load_cpu",
+      "previous_error": "Unrecognized model in BrunoHays/embeddinggemma-2-nullspace-audio. Should have a `model_type` key in its config.json.",
+      "error": "Unrecognized model in BrunoHays/embeddinggemma-2-nullspace-audio. Should have a `model_type` key in its config.json."
+    },
+    {
+      "model": "BAAI/bge-reranker-v2-gemma",
+      "index": 31,
+      "previous_result": "FAIL(output)",
+      "result": "FAIL(output)",
+      "previous_started_at": "2026-11-03T15:34:37.563999+00:00",
+      "started_at": "2026-11-03T16:27:37.150732+00:00",
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+      "error": null
+    },
+    {
+      "model": "Snowflake/snowflake-arctic-embed-m-v2.0",
+      "index": 33,
+      "previous_result": "FAIL(forward)",
+      "result": "FAIL(forward)",
+      "previous_started_at": "2026-11-03T16:00:36.977122+00:00",
+      "started_at": "2026-11-03T16:27:40.804993+00:00",
+      "previous_stage": "cpu_inference",
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+      "error": "index 140685528539888 is out of bounds for dimension 0 with size 14"
+    },
+    {
+      "model": "Qwen/Qwen3-Reranker-8B",
+      "index": 34,
+      "previous_result": "FAIL(output)",
+      "result": "FAIL(output)",
+      "previous_started_at": "2026-11-03T15:36:33.649395+00:00",
+      "started_at": "2026-11-03T16:27:41.821223+00:00",
+      "previous_stage": null,
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+      "previous_error": null,
+      "error": null
+    },
+    {
+      "model": "HukukcuApp/tr-legal-embedding-gemma-2",
+      "index": 54,
+      "previous_result": "FAIL(load)",
+      "result": "FAIL(load)",
+      "previous_started_at": "2026-11-03T15:42:02.918547+00:00",
+      "started_at": "2026-11-03T16:27:42.275977+00:00",
+      "previous_stage": "load_cpu",
+      "stage": "load_cpu",
+      "previous_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",
+      "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"
+    },
+    {
+      "model": "moka-ai/m3e-base",
+      "index": 67,
+      "previous_result": "FAIL(output)",
+      "result": "FAIL(output)",
+      "previous_started_at": "2026-11-03T15:45:11.803493+00:00",
+      "started_at": "2026-11-03T16:27:56.535897+00:00",
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+      "previous_error": null,
+      "error": null
+    },
+    {
+      "model": "jinaai/jina-embeddings-v2-base-en",
+      "index": 70,
+      "previous_result": "FAIL(load)",
+      "result": "FAIL(load)",
+      "previous_started_at": "2026-11-03T15:45:55.385742+00:00",
+      "started_at": "2026-11-03T16:27:57.819913+00:00",
+      "previous_stage": "load_cpu",
+      "stage": "load_cpu",
+      "previous_error": "No module named 'transformers.onnx'",
+      "error": "No module named 'transformers.onnx'"
+    },
+    {
+      "model": "Alibaba-NLP/gte-large-en-v1.5",
+      "index": 73,
+      "previous_result": "FAIL(forward)",
+      "result": "FAIL(forward)",
+      "previous_started_at": "2026-11-03T15:46:09.987170+00:00",
+      "started_at": "2026-11-03T16:28:05.050764+00:00",
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+      "error": "index 755665224 is out of bounds for dimension 0 with size 11"
+    },
+    {
+      "model": "nvidia/NV-Embed-v1",
+      "index": 75,
+      "previous_result": "FAIL(load)",
+      "result": "FAIL(load)",
+      "previous_started_at": "2026-11-03T15:46:17.899843+00:00",
+      "started_at": "2026-11-03T16:30:04.363338+00:00",
+      "previous_stage": "load_cpu",
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+      "previous_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.",
+      "error": "cannot import name 'MISTRAL_INPUTS_DOCSTRING' from 'transformers.models.mistral.modeling_mistral' (/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/mistral/modeling_mistral.py)"
+    },
+    {
+      "model": "Jaume/gemma-2b-embeddings",
+      "index": 77,
+      "previous_result": "FAIL(output)",
+      "result": "FAIL(output)",
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+    {
+      "model": "Alibaba-NLP/gte-multilingual-reranker-base",
+      "index": 78,
+      "previous_result": "FAIL(forward)",
+      "result": "FAIL(forward)",
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+    },
+    {
+      "model": "akhooli/Arabic-SBERT-100K",
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+      "started_at": "2026-11-03T16:28:19.331849+00:00",
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+      "stage": "load_cpu",
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+      "error": "'XLMRobertaLoRA' object has no attribute 'all_tied_weights_keys'"
+    },
+    {
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+      "previous_result": "FAIL(output)",
+      "result": "FAIL(output)",
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+      "started_at": "2026-11-03T16:28:28.113973+00:00",
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+      "error": null
+    },
+    {
+      "model": "vidore/colqwen2.5-v0.2",
+      "index": 89,
+      "previous_result": "FAIL(output)",
+      "result": "FAIL(output)",
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+      "started_at": "2026-11-03T16:28:31.417399+00:00",
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+    },
+    {
+      "model": "jinaai/jina-reranker-v2-base-multilingual",
+      "index": 108,
+      "previous_result": "FAIL(load)",
+      "result": "FAIL(load)",
+      "previous_started_at": "2026-11-03T15:52:03.168120+00:00",
+      "started_at": "2026-11-03T16:28:32.287840+00:00",
+      "previous_stage": "load_cpu",
+      "stage": "load_cpu",
+      "previous_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)",
+      "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)"
+    },
+    {
+      "model": "sentence-transformers/multi-qa-mpnet-base-dot-v1",
+      "index": 112,
+      "previous_result": "FAIL(forward)",
+      "result": "FAIL(forward)",
+      "previous_started_at": "2026-11-03T15:52:37.157163+00:00",
+      "started_at": "2026-11-03T16:28:36.861567+00:00",
+      "previous_stage": "neuron_inference",
+      "stage": "neuron_inference",
+      "previous_error": "Inference tensors do not track version counter.",
+      "error": "Inference tensors do not track version counter."
+    },
+    {
+      "model": "sentence-transformers/paraphrase-MiniLM-L6-v2",
+      "index": 113,
+      "previous_result": "FAIL(output)",
+      "result": "FAIL(output)",
+      "previous_started_at": "2026-11-03T15:52:29.729330+00:00",
+      "started_at": "2026-11-03T16:28:41.932312+00:00",
+      "previous_stage": null,
+      "stage": null,
+      "previous_error": null,
+      "error": null
+    },
+    {
+      "model": "jinaai/jina-embeddings-v2-small-en",
+      "index": 114,
+      "previous_result": "FAIL(load)",
+      "result": "FAIL(load)",
+      "previous_started_at": "2026-11-03T15:52:45.768912+00:00",
+      "started_at": "2026-11-03T16:28:45.116156+00:00",
+      "previous_stage": "load_cpu",
+      "stage": "load_cpu",
+      "previous_error": "No module named 'transformers.onnx'",
+      "error": "No module named 'transformers.onnx'"
+    },
+    {
+      "model": "jhgan/ko-sroberta-multitask",
+      "index": 116,
+      "previous_result": "FAIL(output)",
+      "result": "FAIL(output)",
+      "previous_started_at": "2026-11-03T15:52:52.178170+00:00",
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+      "previous_stage": null,
+      "stage": null,
+      "previous_error": null,
+      "error": null
+    },
+    {
+      "model": "sentence-transformers-testing/stsb-bert-tiny-safetensors",
+      "index": 122,
+      "previous_result": "FAIL(output)",
+      "result": "FAIL(output)",
+      "previous_started_at": "2026-11-03T15:53:27.210620+00:00",
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+      "stage": null,
+      "previous_error": null,
+      "error": null
+    },
+    {
+      "model": "Alibaba-NLP/gte-multilingual-base",
+      "index": 123,
+      "previous_result": "FAIL(forward)",
+      "result": "FAIL(forward)",
+      "previous_started_at": "2026-11-03T15:53:34.948327+00:00",
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+      "stage": "cpu_inference",
+      "previous_error": "index 670466312 is out of bounds for dimension 0 with size 11",
+      "error": "index 1193 is out of bounds for dimension 0 with size 11"
+    },
+    {
+      "model": "nomic-ai/nomic-embed-text-v2-moe",
+      "index": 129,
+      "previous_result": "FAIL(forward)",
+      "result": "FAIL(forward)",
+      "previous_started_at": "2026-11-03T15:54:25.528812+00:00",
+      "started_at": "2026-11-03T16:28:59.211576+00:00",
+      "previous_stage": "cpu_inference",
+      "stage": "cpu_inference",
+      "previous_error": "'NomicBertModel' object has no attribute 'get_extended_attention_mask'",
+      "error": "'NomicBertModel' object has no attribute 'get_extended_attention_mask'"
+    },
+    {
+      "model": "sentence-transformers/msmarco-bert-base-dot-v5",
+      "index": 137,
+      "previous_result": "FAIL(forward)",
+      "result": "FAIL(forward)",
+      "previous_started_at": "2026-11-03T15:55:09.237654+00:00",
+      "started_at": "2026-11-03T16:29:10.989662+00:00",
+      "previous_stage": "neuron_inference",
+      "stage": "neuron_inference",
+      "previous_error": "Inference tensors do not track version counter.",
+      "error": "Inference tensors do not track version counter."
+    },
+    {
+      "model": "Alibaba-NLP/gte-base-en-v1.5",
+      "index": 140,
+      "previous_result": "FAIL(forward)",
+      "result": "FAIL(forward)",
+      "previous_started_at": "2026-11-03T15:55:35.076933+00:00",
+      "started_at": "2026-11-03T16:29:12.754293+00:00",
+      "previous_stage": "cpu_inference",
+      "stage": "cpu_inference",
+      "previous_error": "index 140471200382993 is out of bounds for dimension 0 with size 11",
+      "error": "index 23048696 is out of bounds for dimension 0 with size 11"
+    },
+    {
+      "model": "minishlab/potion-base-8M",
+      "index": 144,
+      "previous_result": "FAIL(output)",
+      "result": "FAIL(output)",
+      "previous_started_at": "2026-11-03T15:56:13.809543+00:00",
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+      "previous_stage": null,
+      "stage": null,
+      "previous_error": null,
+      "error": null
+    },
+    {
+      "model": "TimKond/S-PubMedBert-MedQuAD",
+      "index": 146,
+      "previous_result": "FAIL(output)",
+      "result": "FAIL(output)",
+      "previous_started_at": "2026-11-03T15:56:33.415911+00:00",
+      "started_at": "2026-11-03T16:29:15.091834+00:00",
+      "previous_stage": null,
+      "stage": null,
+      "previous_error": null,
+      "error": null
+    },
+    {
+      "model": "nvidia/NV-Embed-v2",
+      "index": 158,
+      "previous_result": "FAIL(load)",
+      "result": "FAIL(load)",
+      "previous_started_at": "2026-11-03T15:58:12.973659+00:00",
+      "started_at": "2026-11-03T16:29:22.582373+00:00",
+      "previous_stage": "load_cpu",
+      "stage": "load_cpu",
+      "previous_error": "'NVEmbedModel' object has no attribute 'all_tied_weights_keys'",
+      "error": "'NVEmbedModel' object has no attribute 'all_tied_weights_keys'"
+    },
+    {
+      "model": "sentence-transformers/multi-qa-MiniLM-L6-dot-v1",
+      "index": 164,
+      "previous_result": "FAIL(forward)",
+      "result": "FAIL(forward)",
+      "previous_started_at": "2026-11-03T15:59:45.659267+00:00",
+      "started_at": "2026-11-03T16:29:29.177391+00:00",
+      "previous_stage": "neuron_inference",
+      "stage": "neuron_inference",
+      "previous_error": "Inference tensors do not track version counter.",
+      "error": "Inference tensors do not track version counter."
+    }
+  ]
+}

validation/sentence-transformers/2026-11-03-top100/logs/007.log

@@ -7,7 +7,7 @@ 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)
+2026-Nov-03 16:27:23.181404 2938473:2938473  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}
+{"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": "2026-11-03T16:26:48.318127+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": 1.3913734536617994, "prompts": {}, "parameter_dtypes": ["torch.bfloat16"], "cpu_scores": [-2.699960470199585, -1.0288699865341187, -2.2972545623779297, -2.0584821701049805], "cpu_seconds": 1.4555524634197354, "cpu_top_document": 2, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 0.46388536784797907, "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": 0.15859147626906633, "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": 31, "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": 16792596224, "allocator_peak_reserved_bytes": 16848519168, "total_seconds": 50.44789768289775}

validation/sentence-transformers/2026-11-03-top100/logs/021.log

@@ -1,5 +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)
+2026-Nov-03 16:27:20.904398 2938474:2938474  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}
+{"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": "2026-11-03T16:26:48.318264+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": 0.4274421576410532, "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": 0.1396558079868555, "cpu_top_document": 4, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 0.4122119527310133, "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": 0.04447338543832302, "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": 695674433, "peak_categories": {"code": 6654512, "tensors": 606081024, "constants": 3473425, "scratchpad": 67108864, "misc": 9832960, "dma_rings": 2523648}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 587197440, "allocator_peak_reserved_bytes": 606076928, "total_seconds": 47.0560898212716}

validation/sentence-transformers/2026-11-03-top100/logs/023.log

@@ -1,11 +1,6 @@
-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 <module>
-    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 "/tmp/neuron-top100-rerun/runs/023/run.py", line 51, in <module>
+    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'],**SPEC.get('extra_model_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 193, in __init__
@@ -28,35 +23,26 @@ Traceback (most recent call last):
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
     )
     ^
-  File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 1190, in _load_modules
-    modules_json_path = load_file_path(
+  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>...
-        local_files_only=local_files_only,
+        backend=self.backend,
     )
-  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 "/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>...
     )
-  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 <module>\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}
+ValueError: Unrecognized model in litert-community/embeddinggemma-300m. Should have a `model_type` key in its config.json.
+{"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": "2026-11-03T16:26:48.324742+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": "Unrecognized model in litert-community/embeddinggemma-300m. Should have a `model_type` key in its config.json.", "traceback": "Traceback (most recent call last):\n  File \"/tmp/neuron-top100-rerun/runs/023/run.py\", line 51, in <module>\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'],**SPEC.get('extra_model_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 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 litert-community/embeddinggemma-300m. Should have a `model_type` key in its config.json.\n", "result": "FAIL(load)", "total_seconds": 32.182727108709514}

validation/sentence-transformers/2026-11-03-top100/logs/024.log

@@ -1,6 +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)
+2026-Nov-03 16:27:23.382160 2938476:2938476  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}
+{"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": "2026-11-03T16:26:48.323954+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": 0.8875982435420156, "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": 2.1594849564135075, "cpu_top_document": 2, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 1.226473362185061, "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": 0.4109700918197632, "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": 40, "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": 16383648960, "allocator_peak_reserved_bytes": 16414408704, "total_seconds": 51.54317019227892}

validation/sentence-transformers/2026-11-03-top100/logs/029.log

@@ -1,6 +1,6 @@
 Traceback (most recent call last):
-  File "/tmp/neuron-top100-sweep/runs/029/run.py", line 50, in <module>
-    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 "/tmp/neuron-top100-rerun/runs/029/run.py", line 51, in <module>
+    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'],**SPEC.get('extra_model_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 193, in __init__
@@ -45,4 +45,4 @@ Traceback (most recent call last):
     ...<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 <module>\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}
+{"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": "2026-11-03T16:27:22.235996+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": "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-rerun/runs/029/run.py\", line 51, in <module>\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'],**SPEC.get('extra_model_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 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": 18.733008542098105}

validation/sentence-transformers/2026-11-03-top100/logs/031.log

@@ -1,6 +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)
+2026-Nov-03 16:27:53.346466 2939929:2939929  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}
+{"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": "2026-11-03T16:27:37.150732+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": 2.0308772353455424, "prompts": {}, "parameter_dtypes": ["torch.float32"], "cpu_scores": [0.9997572302818298, 0.9997515082359314, 0.9998114705085754, 0.9997087121009827], "cpu_seconds": 2.098253570497036, "cpu_top_document": 3, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 0.4742284342646599, "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": 0.08166952524334192, "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": 15, "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": 10061462912, "allocator_peak_reserved_bytes": 10112466944, "total_seconds": 26.05086704529822}

validation/sentence-transformers/2026-11-03-top100/logs/033.log

@@ -1,10 +1,10 @@
 /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 <module>
+  File "/tmp/neuron-top100-rerun/runs/033/run.py", line 64, in <module>
     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
+  File "/tmp/neuron-top100-rerun/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
@@ -61,5 +61,5 @@ Traceback (most recent call last):
   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 <module>\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}
+IndexError: index 140685528539888 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": "2026-11-03T16:27:40.804993+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": 1.9271560944616795, "prompts": {"query": "query: ", "document": ""}, "parameter_dtypes": ["torch.float32"], "status": "error", "stage": "cpu_inference", "error_type": "IndexError", "error": "index 140685528539888 is out of bounds for dimension 0 with size 14", "traceback": "Traceback (most recent call last):\n  File \"/tmp/neuron-top100-rerun/runs/033/run.py\", line 64, in <module>\n    stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n                                                 ~~~~~^^\n  File \"/tmp/neuron-top100-rerun/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 140685528539888 is out of bounds for dimension 0 with size 14\n", "result": "FAIL(forward)", "total_seconds": 14.150352603755891}

validation/sentence-transformers/2026-11-03-top100/logs/034.log

@@ -1,6 +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)
+2026-Nov-03 16:27:58.358244 2940842:2940842  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}
+{"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": "2026-11-03T16:27:41.821223+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": 0.6515219714492559, "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": 2.2711389483883977, "cpu_top_document": 2, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 0.8582923850044608, "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": 0.24533799476921558, "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": 26, "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": 16467906688, "allocator_peak_reserved_bytes": 16521363456, "total_seconds": 25.253529236651957}

validation/sentence-transformers/2026-11-03-top100/logs/054.log

@@ -1,6 +1,6 @@
 Traceback (most recent call last):
-  File "/tmp/neuron-top100-sweep/runs/054/run.py", line 50, in <module>
-    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 "/tmp/neuron-top100-rerun/runs/054/run.py", line 51, in <module>
+    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'],**SPEC.get('extra_model_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 193, in __init__
@@ -66,4 +66,4 @@ Traceback (most recent call last):
     ...<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 <module>\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}
+{"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": "2026-11-03T16:27:42.275977+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": "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-rerun/runs/054/run.py\", line 51, in <module>\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'],**SPEC.get('extra_model_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 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": 13.635371790267527}

validation/sentence-transformers/2026-11-03-top100/logs/067.log

@@ -1,5 +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)
+2026-Nov-03 16:28:10.265957 2941585:2941585  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}
+{"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": "2026-11-03T16:27:56.535897+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": 0.4231596179306507, "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": 0.11570570152252913, "cpu_top_document": 3, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 0.3781044092029333, "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": 0.0854030791670084, "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": 560932689, "peak_categories": {"code": 6555520, "tensors": 471863296, "constants": 3178513, "scratchpad": 67108864, "misc": 9490112, "dma_rings": 2736384}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 452711936, "allocator_peak_reserved_bytes": 471859200, "total_seconds": 20.959871355444193}

validation/sentence-transformers/2026-11-03-top100/logs/070.log

@@ -1,9 +1,6 @@
-[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 <module>
-    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 "/tmp/neuron-top100-rerun/runs/070/run.py", line 51, in <module>
+    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'],**SPEC.get('extra_model_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 193, in __init__
@@ -59,4 +56,4 @@ Traceback (most recent call last):
   File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_bert_hyphen_implementation/f3ec4cf7de7e561007f27c9efc7148b0bd713f81/configuration_bert.py", line 22, in <module>
     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 <module>\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 \"<frozen importlib._bootstrap_external>\", line 759, in exec_module\n  File \"<frozen importlib._bootstrap>\", 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 <module>\n    from transformers.onnx import OnnxConfig\nModuleNotFoundError: No module named 'transformers.onnx'\n", "result": "FAIL(load)", "total_seconds": 8.849647373892367}
+{"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": "2026-11-03T16:27:57.819913+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": "ModuleNotFoundError", "error": "No module named 'transformers.onnx'", "traceback": "Traceback (most recent call last):\n  File \"/tmp/neuron-top100-rerun/runs/070/run.py\", line 51, in <module>\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'],**SPEC.get('extra_model_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 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 \"<frozen importlib._bootstrap_external>\", line 759, in exec_module\n  File \"<frozen importlib._bootstrap>\", 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 <module>\n    from transformers.onnx import OnnxConfig\nModuleNotFoundError: No module named 'transformers.onnx'\n", "result": "FAIL(load)", "total_seconds": 12.02744938340038}

validation/sentence-transformers/2026-11-03-top100/logs/073.log

@@ -1,17 +1,12 @@
-[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 <module>
+  File "/tmp/neuron-top100-rerun/runs/073/run.py", line 64, in <module>
     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 "/tmp/neuron-top100-rerun/runs/073/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
@@ -66,5 +61,5 @@ Traceback (most recent call last):
   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 <module>\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}
+IndexError: index 755665224 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": "2026-11-03T16:28:05.050764+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": 0.6149875931441784, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "status": "error", "stage": "cpu_inference", "error_type": "IndexError", "error": "index 755665224 is out of bounds for dimension 0 with size 11", "traceback": "Traceback (most recent call last):\n  File \"/tmp/neuron-top100-rerun/runs/073/run.py\", line 64, in <module>\n    stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n                                                 ~~~~~^^\n  File \"/tmp/neuron-top100-rerun/runs/073/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/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 755665224 is out of bounds for dimension 0 with size 11\n", "result": "FAIL(forward)", "total_seconds": 10.126153020188212}

validation/sentence-transformers/2026-11-03-top100/logs/075.log

@@ -1,11 +1,6 @@
-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 <module>
-    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 "/tmp/neuron-nv-embed-v1-rerun/runs/075/run.py", line 51, in <module>
+    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'],**SPEC.get('extra_model_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 193, in __init__
@@ -28,35 +23,41 @@ Traceback (most recent call last):
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
     )
     ^
-  File "/home/jingyahuang/sentence-transformers/sentence_transformers/base/model.py", line 1190, in _load_modules
-    modules_json_path = load_file_path(
+  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,
-    ...<4 lines>...
-        local_files_only=local_files_only,
+    ...<12 lines>...
+        **extra_load_kwargs,
     )
-  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 "/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 "/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 "/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/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 <module>\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}
+  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 "<frozen importlib._bootstrap_external>", line 759, in exec_module
+  File "<frozen importlib._bootstrap>", line 491, in _call_with_frames_removed
+  File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/nvidia/NV_hyphen_Embed_hyphen_v1/2e8b322e2b738a383dae0dde5fa19e0b28a5bb11/modeling_nvembed.py", line 11, in <module>
+    from transformers.models.mistral.modeling_mistral import MISTRAL_INPUTS_DOCSTRING
+ImportError: cannot import name 'MISTRAL_INPUTS_DOCSTRING' from 'transformers.models.mistral.modeling_mistral' (/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/mistral/modeling_mistral.py)
+{"index": 75, "model": "nvidia/NV-Embed-v1", "revision": "2e8b322e2b738a383dae0dde5fa19e0b28a5bb11", "trending_rank": 75, "downloads_rank": null, "class": "SentenceTransformer", "dtype": "bfloat16", "attention": "sdpa", "trust_remote_code": true, "config_kwargs": {}, "excluded": null, "exclusion": null, "reason": "Hub access granted; enable the custom model code required by NV-Embed-v1.", "started_at": "2026-11-03T16:30:04.363338+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": "ImportError", "error": "cannot import name 'MISTRAL_INPUTS_DOCSTRING' from 'transformers.models.mistral.modeling_mistral' (/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/mistral/modeling_mistral.py)", "traceback": "Traceback (most recent call last):\n  File \"/tmp/neuron-nv-embed-v1-rerun/runs/075/run.py\", line 51, in <module>\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'],**SPEC.get('extra_model_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 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 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 \"<frozen importlib._bootstrap_external>\", line 759, in exec_module\n  File \"<frozen importlib._bootstrap>\", line 491, in _call_with_frames_removed\n  File \"/home/jingyahuang/.cache/huggingface/modules/transformers_modules/nvidia/NV_hyphen_Embed_hyphen_v1/2e8b322e2b738a383dae0dde5fa19e0b28a5bb11/modeling_nvembed.py\", line 11, in <module>\n    from transformers.models.mistral.modeling_mistral import MISTRAL_INPUTS_DOCSTRING\nImportError: cannot import name 'MISTRAL_INPUTS_DOCSTRING' from 'transformers.models.mistral.modeling_mistral' (/tmp/st-neuron-sweep/lib/python3.14/site-packages/transformers/models/mistral/modeling_mistral.py)\n", "result": "FAIL(load)", "total_seconds": 13.725843532010913}

validation/sentence-transformers/2026-11-03-top100/logs/077.log

@@ -1,6 +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)
+2026-Nov-03 16:28:21.988818 2942474:2942474  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}
+{"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": "2026-11-03T16:28:11.198209+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": 1.1411347407847643, "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": 1.887984692119062, "cpu_top_document": 3, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 0.6383720831945539, "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": 0.14952720422297716, "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": 18, "sample_interval_seconds": 0.1, "peak_bytes": 10209796217, "peak_categories": {"code": 11395752, "tensors": 10108276736, "constants": 4882449, "scratchpad": 67108864, "misc": 15922624, "dma_rings": 2209792}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 10050966144, "allocator_peak_reserved_bytes": 10108272640, "total_seconds": 19.1534237684682}

validation/sentence-transformers/2026-11-03-top100/logs/078.log

@@ -1,10 +1,10 @@
 /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 <module>
+  File "/tmp/neuron-top100-rerun/runs/078/run.py", line 64, in <module>
     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
+  File "/tmp/neuron-top100-rerun/runs/078/run.py", line 56, 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)
@@ -61,5 +61,5 @@ Traceback (most recent call last):
   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 <module>\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}
+IndexError: index 90194313471 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": "2026-11-03T16:28:16.434610+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": 1.973351868800819, "prompts": {}, "parameter_dtypes": ["torch.float32"], "status": "error", "stage": "cpu_inference", "error_type": "IndexError", "error": "index 90194313471 is out of bounds for dimension 0 with size 32", "traceback": "Traceback (most recent call last):\n  File \"/tmp/neuron-top100-rerun/runs/078/run.py\", line 64, in <module>\n    stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n                                                 ~~~~~^^\n  File \"/tmp/neuron-top100-rerun/runs/078/run.py\", line 56, 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 90194313471 is out of bounds for dimension 0 with size 32\n", "result": "FAIL(forward)", "total_seconds": 9.826986877247691}

validation/sentence-transformers/2026-11-03-top100/logs/079.log

@@ -1,5 +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)
+2026-Nov-03 16:28:27.482344 2943037:2943037  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}
+{"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": "2026-11-03T16:28:19.317175+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": 0.5274149598553777, "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": 0.13939552847296, "cpu_top_document": 4, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 0.35299276281148195, "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": 0.04365590400993824, "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": 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": 15.680451227352023}

validation/sentence-transformers/2026-11-03-top100/logs/081.log

@@ -1,7 +1,7 @@
 [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 <module>
-    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 "/tmp/neuron-top100-rerun/runs/081/run.py", line 51, in <module>
+    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'],**SPEC.get('extra_model_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 193, in __init__
@@ -72,4 +72,4 @@ Traceback (most recent call last):
         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 <module>\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}
+{"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": "2026-11-03T16:28:19.331849+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-rerun/runs/081/run.py\", line 51, in <module>\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'],**SPEC.get('extra_model_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 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": 10.509030694141984}

validation/sentence-transformers/2026-11-03-top100/logs/083.log

@@ -1,5 +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)
+2026-Nov-03 16:28:36.613425 2943706:2943706  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}
+{"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": "2026-11-03T16:28:28.113973+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": 0.3918236820027232, "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": 0.11149388272315264, "cpu_top_document": 4, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 0.44567768834531307, "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": 0.054856122471392155, "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": 699050657, "peak_categories": {"code": 7318992, "tensors": 606081024, "constants": 3440657, "scratchpad": 67108864, "misc": 11850688, "dma_rings": 3250432}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 584563200, "allocator_peak_reserved_bytes": 606076928, "total_seconds": 15.188867619261146}

validation/sentence-transformers/2026-11-03-top100/logs/089.log

@@ -1,8 +1,8 @@
 [transformers] Qwen2_5_VLModel LOAD REPORT from: vidore/colqwen2.5-base
 Key                     | Status     |  | 
 ------------------------+------------+--+-
-custom_text_proj.weight | UNEXPECTED |  | 
 custom_text_proj.bias   | UNEXPECTED |  | 
+custom_text_proj.weight | UNEXPECTED |  | 
 
 Notes:
 - UNEXPECTED:	can be ignored when loading from different task/architecture; not ok if you expect identical arch.
@@ -15,7 +15,7 @@ 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)
+2026-Nov-03 16:28:43.778744 2944185:2944185  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}
+{"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": "2026-11-03T16:28:31.417399+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": 2.2792115388438106, "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": 2.1973909735679626, "cpu_top_document": 4, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 2.5120828673243523, "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": 0.8568719290196896, "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": 51, "sample_interval_seconds": 0.1, "peak_bytes": 15556522617, "peak_categories": {"code": 13058680, "tensors": 15437139968, "constants": 6002945, "scratchpad": 67108864, "misc": 22477824, "dma_rings": 10734336}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 15333555840, "allocator_peak_reserved_bytes": 15437135872, "total_seconds": 24.30755981616676}

validation/sentence-transformers/2026-11-03-top100/logs/108.log

@@ -1,7 +1,7 @@
 [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 <module>
-    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 "/tmp/neuron-top100-rerun/runs/108/run.py", line 51, in <module>
+    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'],**SPEC.get('extra_model_kwargs',{})})
   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__
@@ -61,4 +61,4 @@ Traceback (most recent call last):
   File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_reranker_hyphen_v2_hyphen_base_hyphen_multilingual/9cfeff2df7d40d1b78e75e5e9cebec92a99813c9/embedding.py", line 11, in <module>
     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 <module>\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 \"<frozen importlib._bootstrap_external>\", line 759, in exec_module\n  File \"<frozen importlib._bootstrap>\", 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 <module>\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 <module>\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}
+{"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": "2026-11-03T16:28:32.287840+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": "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-rerun/runs/108/run.py\", line 51, in <module>\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'],**SPEC.get('extra_model_kwargs',{})})\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 \"<frozen importlib._bootstrap_external>\", line 759, in exec_module\n  File \"<frozen importlib._bootstrap>\", 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 <module>\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 <module>\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": 8.39421737473458}

validation/sentence-transformers/2026-11-03-top100/logs/112.log

@@ -1,12 +1,12 @@
 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)
+2026-Nov-03 16:28:44.832058 2944506:2944506  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 <module>
+  File "/tmp/neuron-top100-rerun/runs/112/run.py", line 70, in <module>
     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
+  File "/tmp/neuron-top100-rerun/runs/112/run.py", line 62, 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)
@@ -15,4 +15,4 @@ Traceback (most recent call last):
     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 <module>\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}
+{"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": "2026-11-03T16:28:36.861567+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": 0.3251633159816265, "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": 0.0869925981387496, "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-rerun/runs/112/run.py\", line 70, in <module>\n    stage='neuron_inference';t=time.monotonic();actual=score();r['score_device']=str(actual.device)\n                                                       ~~~~~^^\n  File \"/tmp/neuron-top100-rerun/runs/112/run.py\", line 62, 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": 481622592, "allocator_peak_reserved_bytes": 501219328, "total_seconds": 16.085152969695628}

validation/sentence-transformers/2026-11-03-top100/logs/113.log

@@ -1,5 +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)
+2026-Nov-03 16:28:49.652791 2944770:2944770  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}
+{"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": "2026-11-03T16:28:41.932312+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": 0.28461221139878035, "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": 0.0305560240522027, "cpu_top_document": 3, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 0.3316585561260581, "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": 0.028371094726026058, "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": 15.499813811853528}

validation/sentence-transformers/2026-11-03-top100/logs/114.log

@@ -1,6 +1,6 @@
 Traceback (most recent call last):
-  File "/tmp/neuron-top100-sweep/runs/114/run.py", line 50, in <module>
-    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 "/tmp/neuron-top100-rerun/runs/114/run.py", line 51, in <module>
+    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'],**SPEC.get('extra_model_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 193, in __init__
@@ -56,4 +56,4 @@ Traceback (most recent call last):
   File "/home/jingyahuang/.cache/huggingface/modules/transformers_modules/jinaai/jina_hyphen_bert_hyphen_implementation/f3ec4cf7de7e561007f27c9efc7148b0bd713f81/configuration_bert.py", line 22, in <module>
     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 <module>\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 \"<frozen importlib._bootstrap_external>\", line 759, in exec_module\n  File \"<frozen importlib._bootstrap>\", 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 <module>\n    from transformers.onnx import OnnxConfig\nModuleNotFoundError: No module named 'transformers.onnx'\n", "result": "FAIL(load)", "total_seconds": 8.320869617164135}
+{"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": "2026-11-03T16:28:45.116156+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-rerun/runs/114/run.py\", line 51, in <module>\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'],**SPEC.get('extra_model_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 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 \"<frozen importlib._bootstrap_external>\", line 759, in exec_module\n  File \"<frozen importlib._bootstrap>\", 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 <module>\n    from transformers.onnx import OnnxConfig\nModuleNotFoundError: No module named 'transformers.onnx'\n", "result": "FAIL(load)", "total_seconds": 7.416379694826901}

validation/sentence-transformers/2026-11-03-top100/logs/116.log

@@ -1,5 +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)
+2026-Nov-03 16:29:01.995093 2946484:2946484  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}
+{"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": "2026-11-03T16:28:53.794159+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": 0.3335246341302991, "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": 0.13313346728682518, "cpu_top_document": 4, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 2.8663115464150906, "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": 0.043972715735435486, "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": 31, "sample_interval_seconds": 0.1, "peak_bytes": 602627681, "peak_categories": {"code": 7286160, "tensors": 509612032, "constants": 3866641, "scratchpad": 67108864, "misc": 12000704, "dma_rings": 2753280}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 492353024, "allocator_peak_reserved_bytes": 509607936, "total_seconds": 18.043465487658978}

validation/sentence-transformers/2026-11-03-top100/logs/122.log

@@ -1,5 +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)
+2026-Nov-03 16:29:02.548514 2946508:2946508  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}
+{"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": "2026-11-03T16:28:54.750978+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": 0.25583696737885475, "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": 0.016696914099156857, "cpu_top_document": 4, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 0.31738284416496754, "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": 0.015191987156867981, "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": 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": 14.501598661765456}

validation/sentence-transformers/2026-11-03-top100/logs/123.log

@@ -9,11 +9,12 @@ 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 <module>
+  File "/tmp/neuron-top100-rerun/runs/123/run.py", line 64, in <module>
     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 "/tmp/neuron-top100-rerun/runs/123/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
@@ -68,5 +69,5 @@ Traceback (most recent call last):
   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 <module>\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}
+IndexError: index 1193 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": "2026-11-03T16:28:57.681382+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": 1.974479383789003, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "status": "error", "stage": "cpu_inference", "error_type": "IndexError", "error": "index 1193 is out of bounds for dimension 0 with size 11", "traceback": "Traceback (most recent call last):\n  File \"/tmp/neuron-top100-rerun/runs/123/run.py\", line 64, in <module>\n    stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n                                                 ~~~~~^^\n  File \"/tmp/neuron-top100-rerun/runs/123/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/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 1193 is out of bounds for dimension 0 with size 11\n", "result": "FAIL(forward)", "total_seconds": 13.360865868628025}

validation/sentence-transformers/2026-11-03-top100/logs/129.log

@@ -1,11 +1,12 @@
 /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 <module>
+  File "/tmp/neuron-top100-rerun/runs/129/run.py", line 64, in <module>
     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 "/tmp/neuron-top100-rerun/runs/129/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
@@ -50,4 +51,4 @@ Traceback (most recent call last):
         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 <module>\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}
+{"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": "2026-11-03T16:28:59.211576+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": 4.217651919461787, "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-rerun/runs/129/run.py\", line 64, in <module>\n    stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n                                                 ~~~~~^^\n  File \"/tmp/neuron-top100-rerun/runs/129/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/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": 14.102670108899474}

validation/sentence-transformers/2026-11-03-top100/logs/137.log

@@ -1,12 +1,12 @@
 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)
+2026-Nov-03 16:29:20.481939 2947849:2947849  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 <module>
+  File "/tmp/neuron-top100-rerun/runs/137/run.py", line 70, in <module>
     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
+  File "/tmp/neuron-top100-rerun/runs/137/run.py", line 62, 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)
@@ -15,4 +15,4 @@ Traceback (most recent call last):
     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 <module>\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}
+{"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": "2026-11-03T16:29:10.989662+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": 0.3936761999502778, "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": 0.10769253689795732, "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-rerun/runs/137/run.py\", line 70, in <module>\n    stage='neuron_inference';t=time.monotonic();actual=score();r['score_device']=str(actual.device)\n                                                       ~~~~~^^\n  File \"/tmp/neuron-top100-rerun/runs/137/run.py\", line 62, 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": 588585921, "peak_categories": {"code": 6350192, "tensors": 501223424, "constants": 2850833, "scratchpad": 67108864, "misc": 8545088, "dma_rings": 2507520}, "capacity_bytes": 25769803776}, "allocator_peak_allocated_bytes": 481544192, "allocator_peak_reserved_bytes": 501219328, "total_seconds": 16.502824168652296}

validation/sentence-transformers/2026-11-03-top100/logs/140.log

@@ -1,11 +1,12 @@
 /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 <module>
+  File "/tmp/neuron-top100-rerun/runs/140/run.py", line 64, in <module>
     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 "/tmp/neuron-top100-rerun/runs/140/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
@@ -60,5 +61,5 @@ Traceback (most recent call last):
   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 <module>\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}
+IndexError: index 23048696 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": "2026-11-03T16:29:12.754293+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": 0.5557530513033271, "prompts": {"query": "", "document": ""}, "parameter_dtypes": ["torch.float32"], "status": "error", "stage": "cpu_inference", "error_type": "IndexError", "error": "index 23048696 is out of bounds for dimension 0 with size 11", "traceback": "Traceback (most recent call last):\n  File \"/tmp/neuron-top100-rerun/runs/140/run.py\", line 64, in <module>\n    stage='cpu_inference';t=time.monotonic();cpu=score().detach().float().cpu().reshape(-1)\n                                                 ~~~~~^^\n  File \"/tmp/neuron-top100-rerun/runs/140/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/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 23048696 is out of bounds for dimension 0 with size 11\n", "result": "FAIL(forward)", "total_seconds": 8.462658165954053}

validation/sentence-transformers/2026-11-03-top100/logs/144.log

@@ -1,5 +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)
+2026-Nov-03 16:29:21.667891 2948406:2948406  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}
+{"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": "2026-11-03T16:29:13.720726+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": 0.17954427190124989, "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": 0.016356867738068104, "cpu_top_document": 3, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 0.06938606780022383, "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": 0.007342119701206684, "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": 2, "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": 30251008, "allocator_peak_reserved_bytes": 33554432, "total_seconds": 15.43065809365362}

validation/sentence-transformers/2026-11-03-top100/logs/146.log

@@ -1,5 +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)
+2026-Nov-03 16:29:23.457873 2948419:2948419  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}
+{"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": "2026-11-03T16:29:15.091834+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": 0.5070198401808739, "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": 0.1015954865142703, "cpu_top_document": 3, "model_device": "neuron:0", "score_device": "neuron:0", "neuron_first_seconds": 0.32567631360143423, "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": 0.035069906152784824, "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": 14.539557542651892}

validation/sentence-transformers/2026-11-03-top100/logs/158.log

@@ -1,6 +1,6 @@
 Traceback (most recent call last):
-  File "/tmp/neuron-top100-sweep/runs/158/run.py", line 50, in <module>
-    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 "/tmp/neuron-top100-rerun/runs/158/run.py", line 51, in <module>
+    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'],**SPEC.get('extra_model_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 193, in __init__
@@ -73,4 +73,4 @@ Traceback (most recent call last):
         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 <module>\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}
+{"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": "2026-11-03T16:29:22.582373+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": "'NVEmbedModel' object has no attribute 'all_tied_weights_keys'", "traceback": "Traceback (most recent call last):\n  File \"/tmp/neuron-top100-rerun/runs/158/run.py\", line 51, in <module>\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'],**SPEC.get('extra_model_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 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": 10.885062549263239}

validation/sentence-transformers/2026-11-03-top100/logs/164.log

@@ -1,12 +1,12 @@
 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)
+2026-Nov-03 16:29:37.249477 2949738:2949738  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 <module>
+  File "/tmp/neuron-top100-rerun/runs/164/run.py", line 70, in <module>
     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
+  File "/tmp/neuron-top100-rerun/runs/164/run.py", line 62, 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)
@@ -15,4 +15,4 @@ Traceback (most recent call last):
     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 <module>\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}
+{"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": "2026-11-03T16:29:29.177391+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": 0.3136888975277543, "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": 0.028249465860426426, "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-rerun/runs/164/run.py\", line 70, in <module>\n    stage='neuron_inference';t=time.monotonic();actual=score();r['score_device']=str(actual.device)\n                                                       ~~~~~^^\n  File \"/tmp/neuron-top100-rerun/runs/164/run.py\", line 62, 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": 16.736036530695856}

validation/sentence-transformers/2026-11-03-top100/memory_samples/007.json

@@ -1 +1 @@
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3.0281519470736384, "bytes": 16937250251, "categories": {"code": 8118208, "tensors": 16848523264, "constants": 1605643, "scratchpad": 67108864, "misc": 10510848, "dma_rings": 1383424}}]

validation/sentence-transformers/2026-11-03-top100/memory_samples/024.json

@@ -1 +1 @@
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validation/sentence-transformers/2026-11-03-top100/memory_samples/079.json

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validation/sentence-transformers/2026-11-03-top100/memory_samples/083.json

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validation/sentence-transformers/2026-11-03-top100/memory_samples/112.json

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validation/sentence-transformers/2026-11-03-top100/memory_samples/113.json

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validation/sentence-transformers/2026-11-03-top100/memory_samples/116.json

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validation/sentence-transformers/2026-11-03-top100/memory_samples/122.json

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