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https://api.github.com/repos/huggingface/transformers/issues/37212 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37212/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37212/comments | https://api.github.com/repos/huggingface/transformers/issues/37212/events | https://github.com/huggingface/transformers/pull/37212 | 2,966,869,594 | PR_kwDOCUB6oc6RHZ1O | 37,212 | Fix small bug in PaliGemma demo docs | {
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"merged_at... | # What does this PR do?
Fixes bug in Paligemma usage example
Fixes #37181
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTI... | {
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https://api.github.com/repos/huggingface/transformers/issues/37210 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37210/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37210/comments | https://api.github.com/repos/huggingface/transformers/issues/37210/events | https://github.com/huggingface/transformers/pull/37210 | 2,966,702,303 | PR_kwDOCUB6oc6RG0hg | 37,210 | add fast image processor for pix2struct | {
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# What does this PR do?
add fast image processor for pix2struct
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome... | null | {
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This PR fixes the grad acc issue with gemma3 model. The issue was that we passed **kwargs in the model forward, so we were making the assumption that he was passing `**loss_kwargs` -> `num_items_in_batch` to calculate the loss. Not sure what is the best way to fix this @ArthurZucker in genera... | {
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"merged_at... | Also add notes asking users to set `TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1` or call `torch._dynamo.config.capture_scalar_outputs = True`, as currently this will cause a graph break.
# What does this PR do?
Fix `max_length_q` and `max_length_k` types to `flash_attn_varlen_func`. Also add notes asking users to set `T... | {
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cc @yonigozlan | {
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Similar to #37170, another try to avoid/reduce some remaining CI job failures | {
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- `transformers` version: 4.50.3
- Platform: Linux-5.14.0-284.73.1.el9_2.x86_64-x86_64-with-glibc2.31
- Python version: 3.12.9
- Huggingface_hub version: 0.29.3
- Safetensors version: 0.5.3
- Accelerate version: 1.0.1
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version ... | {
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1. test_resize_tokens_embeddings_with_deepspeed_multi_gpu
2. test_resize_embeddings_untied_with_deepspeed_multi_gpu | {
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transformers==4.50.3
### Who can help?
@osanseviero @ArthurZucker
### Information
- [ ] The official example scripts
- [x] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)
#... | {
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This PR introduces separate limits for saving full checkpoints and model weights in the Trainer class. Currently, save_total_limit applies to both, which can lead to inefficient storage management. This change allows users to:
Retain intermediate model weights for analysis without storing full... | null | {
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I wonder if it is possible to have different limits for saving full checkpoints and model weights.
Currently, only `save_total_limit` control the limits.
### Motivation
Sometimes people need intermediate weights for analysis, but saving full checkpoints take too much space.
`save_only_model` ca... | null | {
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This test fails both on CUDA and XPU.
Root Cause:
The model's output sequence assertion can pass, but the logits assertion fails. This indicates that there might be some numerical precision issues during inference with torch.float16, since the model is loaded with `torch_dtype=torch.float... | {
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- updated model card for Qwen2.
#36979
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#crea... | {
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This PR implements a FastImageProcessor for the the VideoMAE model using BaseImageProcessorFast. Related #36978
Note:
1. I was not able to run `test_can_compile_fast_image_processor` as I'm using a M1 and don't have access to a NVIDIA GPU.
2. The test implemented in the method `test_slo... | null | {
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when run unit test `pytest -rA tests/deepspeed/test_deepspeed.py::TestDeepSpeedWithLauncher::test_clm_from_config_zero3_fp16` on XPU with `spec_xpu.py` by following this [doc](https://huggingface.co/docs/transformers/en/testing). Error with below log
> stderr: Traceback (most recent call last):
> stder... | {
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- Platform: Linux-6.8.0-52-generic-x86_64-with-glibc2.35
- Python version: 3.12.9
- Huggingface_hub version: 0.29.3
- Safetensors version: 0.5.3
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"merged_at... | # What does this PR do?
allow head_dim for qwen2_moe. (qwen2, qwen3, qwen3_moe models are possible currently.)
Fixes #37187
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://git... | {
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allow to use custom head_dim for qwen2_moe. (qwen2, qwen3, qwen3_moe models are possible currently.)
### Motivation
I want to use train model with custom head_dim:
not `self.head_dim = config.hidden_size // config.num_attention_heads`
but `self.head_dim = getattr(config, "head_dim", config.hidden... | {
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- Platform: Linux-6.8.0-1025-gcp-x86_64-with-glibc2.39
- Python version: 3.11.10
- Huggingface_hub version: 0.29.3
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transformers.enable_full_determinism enables deterministic flash attention using `FLASH_ATTENTION_DETERMINISTIC` https://github.com/huggingface/transformers/blob/800510c67bfc5cedd0bb7635648a07f39719be43/src/transformers/trainer_utils.py#L79
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"merged_at... | Fixes #36979
* Updated the Falcon model card
* Did not update Falcon3 as it is not explicitly listed, but can do it also
* Did not include the attention visualizer as I was not able to implement it for Falcon models in a straightforward way.
* First contrib, thank you for your patience <3
## Before submitting... | {
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I am encountering a persistent issue with TapasTokenizer (version 4.50.3) where it consistently produces token_type_ids filled with zeros, even when tokenizing a Pandas DataFrame directly recreated from the first table example in the official fine-tuning tutorial for TAPAS on SQA b... | {
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https://github.com/huggingface/transformers/blob/v4.50.3/docs/source/en/model_doc/paligemma.md#single-image-inference
At the time of writing, this is the default version of the docs people come across via
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Following https://github.com/huggingface/transformers/issues/36978:
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Fixes link to Quark page in quantization docs, the previous link shows 404.
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transfor... | {
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https://github.com/huggingface/transformers/pull/37031 caused much much longer loading times (see https://github.com/huggingface/transformers/issues/37160) basically causing going from ~3/4 min to 10+ hours for Deepseek R1.
I'm fully reverting for now.
I think (not completely sure) the is... | {
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fixes #35597 | null | {
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In v4.45, we set in motion the removal of `GenerationMixin` inheritance by default in `PreTrainedModel`, our base model class. You can recap the full list of reasons in the [original PR](https://github.com/huggingface/transformers/pull/33203), but TL;DR removes circular dependencies and make ... | {
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- `transformers` version: 4.50.3
- Platform: macOS-14.6.1-arm64-arm-64bit
- Python version: 3.12.9
### Who can help?
@eustlb @gante
### Information
- [x] The official example scripts
- [ ] My own modified scripts
### Tasks
- [x] An officially supported task in the `examples` folder (such as GLU... | {
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It'd be great to make the EoMT model available in the Transformers library, because it does image segmentation (instance, semantic and panoptic) in a much simpler way that [Mask2Former](https://huggingface.co/docs/transformers/main/en/model_doc/maskformer) and [OneFormer](https://huggingface.co/d... | {
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Try to avoid pipeline test failing by (potentially) reducing the number of calls to hub. | {
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#36978
Add fast image processor for Swin2SR
cc @yonigozlan | {
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Introduction:
We introduce Quantized Language-Image Pretraining (QLIP), a visual tokenization method that combines state-of-the-art reconstruction quality with state-of-the-art zero-shot image understanding. QLIP trains a binary-spherical-quantization-based autoencoder with reconstruction and la... | null | {
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cc @yonigozlan | {
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Add Optional to more types so that we can enable more RUFF rules on type checking.
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Fixes a regression from https://github.com/huggingface/transformers/pull/36991 whereby resuming training from a checkpoint would fail when attempting to load the rng state. The regression only affects torch versions < 2.6.0.
see https://github.com/axolotl-ai-cloud/axolotl/actions/runs/141857... | {
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```
File "/home/software/anaconda2019/envs/TrOCR/lib/python3.8/site-packages/transformers/models/swinv2/modeling_swinv2.py", line 362,... | {
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Following the recent merged PR and [release note](https://github.com/huggingface/transformers/releases/tag/v4.50.3-DeepSeek-3), I try to load the DeepSeek R1 model using code snippet below on single P5EN (8 H200) GPUs.
1. The first issue I have is that it took very long time to load. Estimation is ~... | {
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"merged_at... | # What does this PR do?
Modify docs to help users determine which quantization methods to use
## Who can review?
@SunMarc @stevhliu | {
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"merged_at... | This PR updates the model card for Mistral and follows the template outlined in the issue. Please let me know if any changes need to be made.
Fixes https://github.com/huggingface/transformers/issues/36979
### Before submitting
- [x] This PR improves the docs.
### Who can review?
@stevhliu
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"merged_at... | # Update LayoutLMv3 Model Card Documentation
This PR updates the LayoutLMv3 model card documentation to follow the standardized format as requested in #36979. The changes improve the documentation's clarity and usability while maintaining consistency with other model cards in the repository.
# What does this PR d... | null | {
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cc @yonigozlan | {
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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As described in the issue, this PR updates the model card for Jamba. I've chosen to also add the newer Jamba-Large-1.6 and Mini models in the model card as well and notes for loading the model using accelerate and BnB. Please let me know if any modifications are required and I will make the n... | {
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`transformers-cli env` output:
- `transformers` version: 4.50.3
- Platform: Linux-6.8.0-52-generic-x86_64-with-glibc2.35
- Python version: 3.10.12
- Huggingface_hub version: 0.29.3
- Safetensors version: 0.5.3
- Accelerate version: 1.5.2
- Accelerate config: not found
- DeepSpeed version: 0.16.4
- P... | {
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Adds support for Baichaun M1
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.... | null | {
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In order to get Trainer support for FSDP2 in `accelerate`, we have to pass the model and optimizer into `Accelerator.prepare()` at the same time (https://github.com/huggingface/accelerate/pull/3394/files#r2017637611).
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The video loading logic was broken after the last feature of `load_audio_from_video`. The condition should not be applied to loading videos, but only to audio from video. The CI didn't catch anything because we don't have `pyav` in general dependencies
The fix is to apply `if/else` to only... | {
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https://api.github.com/repos/huggingface/transformers/issues/37145 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37145/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37145/comments | https://api.github.com/repos/huggingface/transformers/issues/37145/events | https://github.com/huggingface/transformers/pull/37145 | 2,960,669,067 | PR_kwDOCUB6oc6QyUqj | 37,145 | 🌐 [i18n-KO] Translated `siglip.md` to Korean | {
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Translated the `siglip.md` file of the documentation to Korean.
Thank you in advance for your review.
Part of https://github.com/huggingface/transformers/issues/20179
## Before reviewing
- [x] Check for missing / redundant translations (번역 누락/중복 검사)
- [x] Grammar Check (맞춤법 검사)
- [x... | {
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https://api.github.com/repos/huggingface/transformers/issues/37143 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37143/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37143/comments | https://api.github.com/repos/huggingface/transformers/issues/37143/events | https://github.com/huggingface/transformers/pull/37143 | 2,960,607,850 | PR_kwDOCUB6oc6QyHRh | 37,143 | Add Fast Image Processor for mobileViT | {
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"merged_at... | related to #36978
cc: @yonigozlan
I added Fast image processor for mobileViT and I noticed a noticeable difference between the outputs after preprocessing.
Here’s the code I used to compare them:
```
diff = (encoding_slow.pixel_values - encoding_fast.pixel_values).abs()
print(f"\n📊 Difference statistics:")... | {
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skippppppppppppppp for now | {
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"merged_at... | # What does this PR do?
Add Fast Image Processor for Chameleon (Issue [#36978](https://github.com/huggingface/transformers/issues/36978)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [X] Did you read the [contributor guideline](http... | {
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Remove rope related warnings when loading DeepSeek-V3 checkpoints.
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https://api.github.com/repos/huggingface/transformers/issues/37138 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37138/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37138/comments | https://api.github.com/repos/huggingface/transformers/issues/37138/events | https://github.com/huggingface/transformers/pull/37138 | 2,960,434,286 | PR_kwDOCUB6oc6QxhNC | 37,138 | [don't merge] debug audio pipeline | {
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debug | {
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https://api.github.com/repos/huggingface/transformers/issues/37137 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37137/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37137/comments | https://api.github.com/repos/huggingface/transformers/issues/37137/events | https://github.com/huggingface/transformers/pull/37137 | 2,960,420,937 | PR_kwDOCUB6oc6QxeS3 | 37,137 | bump Torch 2.1 with broken compatibility `torch.compile` | {
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This PR updates the minimum required version of Torch to 2.1 due to an issue with `torch.compile` in 2.0. The problem was identified through Dependabot in [#3027](https://github.com/Lightning-AI/torchmetrics/pull/3027), where all versions passed except for 2.0.
Fixes #37238
Issue Detail... | {
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This is a temporary fix, while seeing if we can refactor hqq and b&b 4bits to work without the full state dict but only a given param one at a time. | {
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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I tried loading Deepseek-V3 with the library code following #35926 but I got the following errors when loading the config:
```
`rope_scaling`'s factor field must be a float >= 1, got 40
`rope_scaling`'s beta_fast field must be a float, got 32
`rope_scaling`'s beta_slow field must be a float, got 1
```... | {
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Following https://github.com/huggingface/transformers/pull/35926 and https://github.com/huggingface/transformers/pull/37086, make the quantizers work with a state dict on meta device.
See https://github.com/huggingface/transformers/pull/37086 for the issue at hand
Currently, will lead to ... | {
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"merged_at... | To reproduce:
`TRANSFORMERS_TEST_DEVICE=xpu ZE_AFFINITY_MASK=0 RUN_SLOW=1 pytest -rA tests/models/llava/test_modeling_llava.py::LlavaForConditionalGenerationIntegrationTest::test_pixtral_4bit`
Hi @SunMarc . This PR fixed llava tests on XPU because the output slightly differs from cuda. Please review it. Thanks! | {
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- `transformers` version: 4.50.3
- Platform: Linux-5.15.0-91-generic-x86_64-with-glibc2.35
- Python version: 3.11.10
- Huggingface_hub version: 0.26.2
- Safetensors version: 0.4.5
- Accelerate version: 1.0.1
- Accelerate config: - compute_environment: LOCAL_MACHINE
- distributed_type: MULTI_... | {
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https://api.github.com/repos/huggingface/transformers/issues/37127 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37127/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37127/comments | https://api.github.com/repos/huggingface/transformers/issues/37127/events | https://github.com/huggingface/transformers/pull/37127 | 2,959,533,370 | PR_kwDOCUB6oc6Qufib | 37,127 | refactor(audio_processing): replace pipe with temp files for FFmpeg p… | {
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"merged_at... | …rocessing
This change replaces the previous pipe-based FFmpeg audio decoding approach
with temporary file operations to improve reliability, especially for
container formats like MP4/m4a.
Key reasons for this change:
1. MP4 container format requires random access to metadata (moov atoms) which... | null | {
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"merged_at... | case 1: pytest -rA tests/models/llama/test_modeling_llama.py::LlamaIntegrationTest::test_model_7b_logits
case 2: pytest -rA tests/models/llama/test_modeling_llama.py::LlamaIntegrationTest::test_model_7b_logits_bf16
both don't have XPU criteria, put them as key 0 and reuse A100/A100 ground truth. Both can pass in P... | {
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I'm working on PD disaggregation where I'm trying to pass KV cache produced in GPU to CPU before sending them to decode process, looks like the following implementation doesn't have a way to move once created, is that the case? If so, is it possible to add an API to do that?
https://github.com/hug... | {
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In this code, char_seq_length is guaranteed to be an integer, so there is no need to cast it to tensor. By removing this, canine model is now exportable.
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the relea... | {
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Previously, the identity function was used for dropped tokens with a weight from the expert that was not applied to the hidden states. This was misleading, because dropping means, the expert weight is zero. Instead of trying to fix the weight, we take an easier approach by initializing with z... | {
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- `transformers` version: 4.51.0.dev0 (Commit 0d6a60f)
- Platform: Linux-5.14.0-503.22.1.el9_5.x86_64-x86_64-with-glibc2.35
- Python version: 3.11.11
- Huggingface_hub version: 0.29.3
- Safetensors version: 0.5.3
- Accelerate version: 1.5.1
- Accelerate config: not found
- DeepSpeed version: not ins... | {
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"merged_at... | **Symptom**
`pytest -rA tests/generation/test_logits_process.py::LogitsProcessorTest::test_watermarking_processor` will assert out with below logs while running on XPU.
> elf.assertTrue((out[:, 1] == scores_wo_bias + watermark.bias).all())
> E AssertionError: tensor(False, device='xpu:0') is not true
**... | {
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"merged_at... | # Add FastImageProcessor for EfficientNet
## What does this PR do?
This PR implements a `FastImageProcessor` for the `EfficientNet` model using `BaseImageProcessorFast`.
- Added `EfficientNetImageProcessorFast` to support fast GPU-based preprocessing using PyTorch/Torchvision ops
- Verified default values (e.... | null | {
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```
model_name = "meta-llama/Llama-3.2-1B-Instruct"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto", torch_dtype=torch.float16)
@app.post("/unfluff")
async def unfluff_llm(unfluff_request: UnfluffRequest):
... | {
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Here I noticed a normalization over sqrt(text_hidden_dim), why is this?
And I do not see this line in official big_vision implementation. | {
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https://api.github.com/repos/huggingface/transformers/issues/37116 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37116/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37116/comments | https://api.github.com/repos/huggingface/transformers/issues/37116/events | https://github.com/huggingface/transformers/issues/37116 | 2,958,972,148 | I_kwDOCUB6oc6wXlT0 | 37,116 | modernBERT Duplicate Template Name | {
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transformers 4.50.3
torch 2.6.0
python 3.11
MacOS 15.3.2
Trying to run a simple test in a notebook I get the following error:
RuntimeError: Failed to import transformers.models.modernbert.modeling_modernbert because of the following error (look up to see its traceback):
duplicate template name
I have... | {
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https://api.github.com/repos/huggingface/transformers/issues/37115 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37115/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37115/comments | https://api.github.com/repos/huggingface/transformers/issues/37115/events | https://github.com/huggingface/transformers/pull/37115 | 2,958,861,221 | PR_kwDOCUB6oc6QsWOs | 37,115 | chore: Update model doc for code_llama | {
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"merged_at... | # What does this PR do?
aims to handle https://github.com/huggingface/transformers/issues/36979#issuecomment-2758560598
sub part of https://github.com/huggingface/transformers/issues/36979
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"merged_at... | `RwKvModel.forward` is supposed to warn if `attention_mask` is passed. Right now the check is `attention_mask is None` which I assume was supposed to be `attention_mask is not None`, which this PR fixes. @gante | {
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https://api.github.com/repos/huggingface/transformers/issues/37113 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37113/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37113/comments | https://api.github.com/repos/huggingface/transformers/issues/37113/events | https://github.com/huggingface/transformers/pull/37113 | 2,958,776,006 | PR_kwDOCUB6oc6QsFUD | 37,113 | Add Fast Mobilenet-V2 Processor | {
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cc @yonigozlan | {
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https://api.github.com/repos/huggingface/transformers/issues/37112 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37112/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37112/comments | https://api.github.com/repos/huggingface/transformers/issues/37112/events | https://github.com/huggingface/transformers/pull/37112 | 2,958,718,081 | PR_kwDOCUB6oc6Qr6Gl | 37,112 | Add Fast Image Processors for mobileViT | {
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cc: @yonigozlan
I added Fast image processor for mobileViT and I noticed a noticeable difference between the outputs after preprocessing.
Here’s the code I used to compare them:
```
diff = (encoding_slow.pixel_values - encoding_fast.pixel_values).abs()
print(f"\n📊 Difference statistics:")... | {
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