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Align with convention since we can 🤗 | {
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Adds the following to #38443
- Streaming tool calls
- Persistent KV cache across server calls
- BC `chat` generation parameterization
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### System Info
(Colab)
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## Speeding up the encoder
[Reverting](https://github.com/huggingface/transformers/pull/36801#discussion_r2013681886) Shaw's positional embedding calculation to einsum results in a significant speedup in both inference/training runtime.
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Operating System: Linux
Python Version: 3.10.16
Transformers Library Version: 4.51.0
Hardware Configuration: GPU A100
### Who can help?
_No response_
### Information
- [x] The official example scripts
- [ ] My own modified scripts
### Tasks
- [x] An officially supported task in the `examples` ... | {
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This PR adds a new audio classification model: MatchboxNet, implementing the 1D Time-Channel Separable Convolutional Neural Network architecture for keyword spotting / speech commands recognition as described in the paper:
> MatchboxNet: 1D Time-Channel Separable Convolutional Neural Network... | {
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https://api.github.com/repos/huggingface/transformers/issues/39024 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39024/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39024/comments | https://api.github.com/repos/huggingface/transformers/issues/39024/events | https://github.com/huggingface/transformers/pull/39024 | 3,173,928,439 | PR_kwDOCUB6oc6b-Acq | 39,024 | switch default xpu tp backend to pytorch built-in XCCL from pytorch 2.8 | {
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https://api.github.com/repos/huggingface/transformers/issues/39023 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39023/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39023/comments | https://api.github.com/repos/huggingface/transformers/issues/39023/events | https://github.com/huggingface/transformers/issues/39023 | 3,173,628,056 | I_kwDOCUB6oc69KbiY | 39,023 | Does Gemma 3 need positions ids to be 1-indexed explicitly? | {
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At some point `Gemma3ForConditionalGeneration` used to impose a 1-indexing of `position_ids`, [see here](https://github.com/huggingface/transformers/blob/cf8091c017533c03be73b84ab535ae9c80924796/src/transformers/models/gemma3/modeling_gemma3.py#L1430). However you won't find this in the latest main anymore, [s... | {
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https://api.github.com/repos/huggingface/transformers/issues/39022 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39022/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39022/comments | https://api.github.com/repos/huggingface/transformers/issues/39022/events | https://github.com/huggingface/transformers/issues/39022 | 3,173,580,651 | I_kwDOCUB6oc69KP9r | 39,022 | AssertionError: The parameter 666 has already been reduced Gradient computed twice for this partition. Multiple gradient reduction is currently not supported | {
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I am getting the following error when using SFT + unsloth + DS-2
```
AssertionError: The parameter 666 has already been reduced.
Gradient computed twice for this partition.
Multiple gradient reduction is currently not supported
```
Which seems to be re... | {
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https://api.github.com/repos/huggingface/transformers/issues/39021 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39021/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39021/comments | https://api.github.com/repos/huggingface/transformers/issues/39021/events | https://github.com/huggingface/transformers/pull/39021 | 3,173,425,528 | PR_kwDOCUB6oc6b8W_D | 39,021 | [LightGlue] Fixed attribute usage from descriptor_dim to keypoint_detector_descriptor_dim | {
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Noticed that the first reshapes use the `descriptor_dim` attribute but at this stage, the keypoint descriptors are not fed through the `input_projection` layer, so the keypoint descriptors at this stage have a dimension provided by the keypoint detector, and not the dimension of the descripto... | {
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## 🧠 Overview:
I'm encountering a **segmentation fault** when running the model `finiteautomata/beto-sentiment-analysis` using `AutoModelForSequenceClassification` on a **MacBook Pro with Apple M4**, even when forcing CPU-only execution.
This happens during inference (`model(**inputs)`) with valid i... | {
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"merged_at... | # What does this PR do?
This PR aims to address the issue raised in #39018: a grammatical error on the 'Load Model' page.
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https://api.github.com/repos/huggingface/transformers/issues/39018 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39018/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39018/comments | https://api.github.com/repos/huggingface/transformers/issues/39018/events | https://github.com/huggingface/transformers/issues/39018 | 3,173,152,883 | I_kwDOCUB6oc69Inhz | 39,018 | Grammatical error in the "Loading model's" page | {
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"Call from_pretrained() to download and load a models weights and configuration stored on the Hugging Face Hub."
This should be corrected to:
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when using torch.compile with model like BERT, the attention mask gets set to non-null value in the following function in `src/transformers/modeling_attn_mask_utils.py`. Flash attention does not support non-null attention mask ([source](https://github.com/pytorch/pytorch/blob/b09bd414a6ccba158c09f586a2... | {
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In the current GPT2 implementation, the LMHead module processes all tokens during prefill, even though only the final token’s output is used for generation. This PR aligns the behavior with LlamaModel by computing the LMHead output only for the last token, reducing unnecessary computation dur... | {
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"merged_at... | #38916 was missing a test. We check that custom generate from a local dir with relative imports works properly.
The test is not conventional, so I appreciate the review :) | {
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"merged_at... | Fixes https://huntr.com/bounties/6a6c933f-9ce8-4ded-8b3b-2c1444c61f36 and https://huntr.com/bounties/287d15a7-6e7c-45d2-8c05-11e305776f1f
The Marian change should be 100% identical, and a lot more performant than using a regex. The TF change has a slight behaviour change if people are passing regex patterns in that ... | {
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"merged_at... | `DeepseekV3ModelTest::test_torch_compile_for_training` fails with `torch._dynamo.exc.Unsupported: Dynamic shape operator`. Attempting to remedy by `torch._dynamo.config` flags.
Pytorch was struggling to capture the graph when we were using `if token_indices.numel() > 0:`, so I switched to only loop over the experts... | null | {
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"merged_at... | Refactors the `@auto_docstring` docs:
* adds a link to it from the `modular_transformers.md` doc to help with documentation when contributing a model
* reorganizes sections to start with practical examples of how to use the decorator, documenting arguments, and checking the docstrings first
* remove the emojis and... | {
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"merged_at... | # What does this PR do?
Skips `DeepseekV3ModelTest::test_sdpa_can_dispatch_on_flash` because the head dims are not supported.
### Context
Previously `DeepseekV3ModelTest::test_sdpa_can_dispatch_on_flash` failed with the error `RuntimeError: No available kernel. Aborting execution.`.
Peeking into the logs we find ... | {
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"merged_at... | Generate does not need gradients which is not propagated correctly for a few edge cases when the function itself is inherited and no super call is made. It a TIL for me :D
Not the most important PR but should be done nonetheless imo. | {
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https://api.github.com/repos/huggingface/transformers/issues/39007 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39007/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39007/comments | https://api.github.com/repos/huggingface/transformers/issues/39007/events | https://github.com/huggingface/transformers/issues/39007 | 3,172,562,934 | I_kwDOCUB6oc69GXf2 | 39,007 | 'Mistral3Model' object has no attribute 'prepare_inputs_for_generation' | {
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```bash
transformers==4.53.0.dev0
peft==0.15.2
```
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [ ] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give de... | {
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"merged_at... | There's a bug in smolvlm2 video processing (but keep reading, there's more): the list of frames that make up the prompt is malformed. While debugging transformers `v4.52.4`, this appeared to be because the `return_row_col_info` was removed from the kwargs, possibly in #38105.
**However**, this fix only works if we a... | {
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https://api.github.com/repos/huggingface/transformers/issues/39005 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39005/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39005/comments | https://api.github.com/repos/huggingface/transformers/issues/39005/events | https://github.com/huggingface/transformers/pull/39005 | 3,172,307,262 | PR_kwDOCUB6oc6b4nht | 39,005 | Fix undeterministic order in modular dependencies | {
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"merged_at... | # What does this PR do?
As per the title. This is an edge case that wasn't detected before (I just had the issue with Glm4v, which is why I'm opening the PR) - since the input to the function is a `set`, we need to sort it so that it stays deterministic when we loop afterwards. Otherwise, several runs of the convert... | {
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- `transformers` version: 4.52.3
- Platform: Linux-6.8.0-60-generic-x86_64-with-glibc2.35
- Python version: 3.10.13
- Huggingface_hub version: 0.32.2
- Safetensors version: 0.5.3
- Accelerate version: 1.4.0
- Accelerate config: - compute_environment: LOCAL_MACHINE
- distributed_type: MULTI_G... | {
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https://api.github.com/repos/huggingface/transformers/issues/39003 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39003/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39003/comments | https://api.github.com/repos/huggingface/transformers/issues/39003/events | https://github.com/huggingface/transformers/pull/39003 | 3,172,075,370 | PR_kwDOCUB6oc6b31Ng | 39,003 | refactor: remove custom BarkLayerNorm | {
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"merged_at... | # What does this PR do?
`nn.LayerNorm` supports `bias=False` since Pytorch 2.1, so the custom version is not needed anymore: https://docs.pytorch.org/docs/2.1/generated/torch.nn.LayerNorm.html
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the cas... | {
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https://api.github.com/repos/huggingface/transformers/issues/39002 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39002/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39002/comments | https://api.github.com/repos/huggingface/transformers/issues/39002/events | https://github.com/huggingface/transformers/pull/39002 | 3,172,057,568 | PR_kwDOCUB6oc6b3xWn | 39,002 | [HPU][Critical Issue Fix] ThreadPool instead of Pool for parallel pre-processing | {
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"merged_at... | There had been a problem with Gaudi (HPU) handling multiprocessed pre-processing which was patched with https://github.com/huggingface/transformers/pull/38790
Indeed there're limitations when different processes try to use one HPU device.
So I changed `Pool` which is based on creating new processes with `ThreadPool... | {
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https://api.github.com/repos/huggingface/transformers/issues/39001 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39001/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39001/comments | https://api.github.com/repos/huggingface/transformers/issues/39001/events | https://github.com/huggingface/transformers/pull/39001 | 3,171,970,526 | PR_kwDOCUB6oc6b3emY | 39,001 | Fixes for Arcee model | {
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"merged_at... | # What does this PR do?
As per the title. The TP plan was wrong, this is now fixed. Also simplify a bit the modular (docstrings are not needed as we have `auto_docstring` anyway)
cc @Crystalcareai @pranav4501 for viz if you want 😉
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https://api.github.com/repos/huggingface/transformers/issues/39000 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39000/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39000/comments | https://api.github.com/repos/huggingface/transformers/issues/39000/events | https://github.com/huggingface/transformers/pull/39000 | 3,171,389,935 | PR_kwDOCUB6oc6b1g4e | 39,000 | [generate] document non-canonical beam search default behavior | {
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Related to #38778: this PR adds more context behind some legacy decisions that shouldn't be broken for BC purposes. | {
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https://api.github.com/repos/huggingface/transformers/issues/38999 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38999/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38999/comments | https://api.github.com/repos/huggingface/transformers/issues/38999/events | https://github.com/huggingface/transformers/pull/38999 | 3,170,235,840 | PR_kwDOCUB6oc6bxktE | 38,999 | Use deep copies instead of shallow copies for bbox_embed in GroundingDINO decoder (#37333). | {
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"merged_at... | Fixes [#37333](https://github.com/huggingface/transformers/issues/37333)
The decoder was using shallow copies of `GroundingDinoMLPPredictionHead`, causing all `bbox_embed` layers to share the same instance, which led to unintended parameter sharing. This PR updates it to use `copy.deepcopy()`.
### What I Changed
... | {
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I’ve updat... | {
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Hello, here is a snippet of code that leads to an error with transformers 4.52.4, but worked fine with 4.48.3.
```
from transformers import AutoModelForImageClassification, AutoConfig
pretrained_model="timm/tiny_vit_21m_512.dist_in22k_ft_in1k"
config = AutoConfig.from_pretrained(pretrained_model)
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"merged_at... | Follows up on internal discussion (cc @Vaibhavs10) about clarifying `add_new_model.md` and `modular_transformers.md` by:
* renaming `modular_transformers.md` in the toctree to "Contributing a new model to Transformers" so users easily understand what the doc is versus "Modular Transformers" which may not be as clear... | {
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https://api.github.com/repos/huggingface/transformers/issues/38994 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38994/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38994/comments | https://api.github.com/repos/huggingface/transformers/issues/38994/events | https://github.com/huggingface/transformers/pull/38994 | 3,169,181,811 | PR_kwDOCUB6oc6buGAd | 38,994 | [Modeling] Fix encoder CPU offloading for whisper | {
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"merged_at... | ## Purpose ##
* Fix CPU offloading for WhisperEncoder
* This supports downstream applications which offload the layers of even small models like whisper. See https://github.com/vllm-project/llm-compressor/pull/1263
Without this change, attempting to CPU offload the encoder layer raises a device error
```
Runti... | {
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"merged_at... | - Add is_flash_attn_v2_available() function to check for Flash Attention v2 support
- Implement _flash_attention_v2_forward with support for padding, causal masking, and sliding window
- Add comprehensive test suite for Flash Attention v2 functionality
- Update __init__.py files to expose the new functionality
# ... | {
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- Added config update after wandb.init()
- Verified with run_glue.py in WANDB_MODE=offline | {
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"merged_at... | # What does this PR do?
<!--
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 contribution.
Then, please replace this w... | null | {
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https://api.github.com/repos/huggingface/transformers/issues/38989 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38989/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38989/comments | https://api.github.com/repos/huggingface/transformers/issues/38989/events | https://github.com/huggingface/transformers/pull/38989 | 3,168,767,693 | PR_kwDOCUB6oc6bsru2 | 38,989 | fix `mistral3` tests | {
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"merged_at... | # What does this PR do?
Mistral3's processor will return different prompt on different days, something like
```
Your knowledge base was last updated on 2023-10-01. The current date is 2025-06-24.
```
see the date at the end.
This PR patched the `processor.chat_templat` to always have ` 2025-06-20` and upd... | {
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We should check docstring in modular files as well! Otherwise, most of the time if the docstring is wrong in modular, e.g. in a Config, `make fix-copies` will apply modular with wrong docstring, then `check_docstring` will fix it, but we still have inconsistency between the modular (which was... | null | {
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Extend `BatchEncoding.to()` to also work for nested elements.
When using voice presets in Bark, the processor returns a `BatchEncoding` of
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<summary> System Info transformers env output </summary>
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Those are artifacts of `make style`
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As per the title. Allows to do `python modular_model_converter.py <model>` instead of always `python modular_model_converter.py --files_to_parse <model>`.
cc @ArthurZucker | {
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Mostly update expected values and use `cleanup` to avoid OOM.
See some details in a few comments. | {
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"merged_at... | # What does this PR do?
Fixes #38975
This PR passes `device` to tensor initialization, so to fix the `torch.export` error when the model is on GPU. Otherwise, dynamo will throw errors like `Unhandled FakeTensor Device Propagation for aten.embedding.default, found two different devices cuda:0, cpu'`
This PR m... | {
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transformer version: latest main 3d2c6b90914823c78809874f56e3dfecb1b7105c (06/23)
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [x] My own modified scripts
### Tasks
- [x] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ... | {
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"merged_at... | # What does this PR do?
As per title, refactors attention implementation setting and makes it a public API. We should encourage users to `model.set_attn_implementation()` whenever they want to change it after loading the model, instead of setting config's private attr `model.config._attn_implementation="sdpa"`
Af... | {
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my env list:
archspec 0.2.5
boltons 24.0.0
Brotli 1.1.0
certifi 2025.4.26
cffi 1.17.1
charset-normalizer 3.4.2
colorama 0.4.6
conda 25.3.0
conda-libmamba-solver 25.3.0
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"merged_at... | Supports Flash Attention 3 for `_flash_attention_forward`
Previous https://github.com/huggingface/transformers/pull/36190 @ArthurZucker
Parity test Flash Attention {2,3} based on https://github.com/sgl-project/sglang/blob/main/test/srt/models/test_generation_models.py
```python
$ RUN_SLOW=1 pytest -s tests/gene... | {
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"merged_at... | # What does this PR do?
This PR replaces the PEGASUS-X model card with a new model card matching the format introduced in #36979.
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
## Who can review?
@stevhliu
## Notes
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Hi 🤗 Transformers team,
I would like to contribute a new model to the library:
GLASS – A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization
📄 Paper: https://arxiv.org/abs/2407.09359
💻 Code: https://github.com/cqylunlun/GLASS
GLASS is a... | {
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- transformers version: 4.52.4
- Platform: Linux-5.4.0-215-generic-x86_64-with-glibc2.31
- Python version: 3.11.11
- Accelerate version: 1.8.1
- Wandb version: 0.20.1
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [x] My own modified scripts
### Tasks
- [ ] A... | {
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"merged_at... | This PR adds the new ModernBERTDecoder architecture: it's ModernBERT but trained from scratch as a CLM! This replaces my attempt in #35946 to fit them all in one class. Instead I'll have a script to convert them from encoders to decoders and vice versa by renaming the class and head name (`head` vs `lm_head`)
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Nemotron-H is a family of hybrid Mamba-Transformer models developed by NVIDIA that combines the efficiency of Mamba layers with the accuracy of Transformer architecture. The models come in two sizes:
- 8B parameter model
- 56B/47B parameter models (with a compressed 47B version using MiniPuzzle c... | null | {
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I've noticed that ModernBERT [does not have an implementation in tensorflow](https://github.com/huggingface/transformers/issues/37128#issuecomment-2766235185) and I was looking into it.
I'm checking this https://huggingface.co/docs/transformers/main/add_tensorflow_model and I noticed that it's talking abo... | {
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- fixed a typo in the Mixed precision section for the `TrainingArguments` class configuration with `bf16` dtype
- fixed/synced summary table with the outlines: I believe it should have been SDPA (Scaled dot product attention) and not PEFT.
I've also edited yes/yes for SDPA for both memory ... | {
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- `transformers` version: 4.53.0.dev0
- Platform: Linux-5.4.0-113-generic-x86_64-with-glibc2.39
- Python version: 3.10.18
- Huggingface_hub version: 0.33.0
- Safetensors version: 0.5.3
- Accelerate version: 1.7.0
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (ac... | {
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Introduce a **failure-safe training mode** in the `Trainer` API (e.g., via a flag like `enable_emergency_checkpoint=True`) that ensures training progress is saved **automatically upon unexpected failure**, such as hardware interruptions, out-of-memory errors, or bugs during training. This allows us... | null | {
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"merged_at... | feat: Add Number Token Loss (NTL) implementation
Issue: #38950
Add Number Token Loss (NTL) to improve language model performance on numerical tasks.
NTL addresses the fundamental limitation of cross-entropy loss on numerical tokens
by incorporating ordinal information into the training objective.
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# What does this PR do?
This PR aims to resolve #38918 by guiding users on how to authenticate their Hugging Face accounts using IDEs (PyCharm, VS Code, etc.).
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you may already know this, but I couldn't find the issue anywhere on your GitHub issues, nor Deepspeed's.
The fix is pretty easy, just upgrade the transformers version. But thought it might be worth adding an issue here so someone else finds a fix faster then I did when they start googling.
```
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**Summary:** We suggest to integrate a novel loss, called **Number Token Loss**, to appear at [ICML 2025](https://ibm.biz/ntl-paper).
NTL computes a regression-like loss directly on the token level of a LMHead. **Experiments show that CE augmented with NTL forms a significantly better pretraining o... | null | {
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cc @ArthurZucker | {
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This PR overhauls everything. Ever... | {
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"merged_at... | This PR brings to main a fix that was added in `amd-hf-ci-branch` here: https://github.com/huggingface/transformers/pull/38540
The fix aims to correct a failure of `torch.compile` when compiling a torchvision `resize` function with an uint8 input. The failing tests were:
```
tests/models/internvl/test_video_process... | {
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"merged_at... | # What does this PR do?
Without it, the following would run correctly:
```python
from transformers import AutoModelForCausalLM
import torch
model_id = "hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4"
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="cpu", torch_dtype=torch.bfloat16)
``... | {
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Follow-up to #38758
This PR removes TF tests with the `require_tf` decorator. All uses of `require_tf` were removed, and a deprecation message was added to this test-related function.
(If this PR is approved, I'll open similar PRs for other related decorators, such as `require_flax`) | {
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Some test were no... | {
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Fixes https://github.com/huggingface/transformers/issues/38771.
This PR decouples device_map='auto' and tp_plan='auto'. Before, launching a distributed run when the `device_map` was set to "auto" triggered TP. We removed that and the user should instead pass tp_plan="auto" or tp_size to tig... | {
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This PR pins the PyTorch version for the built Docker containers to 2.6.0. The reason behind this is that the ROCm version of PyTorch 2.7.1 is not available to date and the vanilla install replaces it with the 2.7.1 Nvidia version.
This should be a temporary fix until 2.7.1 is released for... | {
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- Platform: Linux-4.18.0-147.mt20200626.413.el8_1.x86_64-x86_64-with-glibc2.17
- Python version: 3.12.3
- Huggingface_hub version: 0.30.1
- Safetensors version: 0.5.3
- Accelerate version: 1.6.0
- Accelerate config: not found
- DeepSpeed version: 0.16.7
- PyTorc... | {
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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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https://api.github.com/repos/huggingface/transformers/issues/38936 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38936/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38936/comments | https://api.github.com/repos/huggingface/transformers/issues/38936/events | https://github.com/huggingface/transformers/pull/38936 | 3,162,546,206 | PR_kwDOCUB6oc6bYDnB | 38,936 | Switch to use A10 progressively | {
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I don't want to switch in one go. My goal is to switch those job to use A10 if they have no extra failures on A10 compared to T4.
For those have extra failures on A10, I will fix them and switch to A10 progressively.
Currently, the data fetched is from
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- Platform: Linux-6.1.134.1.fi-x86_64-with-glibc2.28
- Python version: 3.12.5
- Huggingface_hub version: 0.33.0
- Safetensors version: 0.5.3
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