Update transformers to 4.40.2

[pyup-bot]

This PR updates transformers from 4.39.3 to 4.40.2.

Changelog

4.40.2

Fix torch fx for LLama model
- Fix for Neuron (30259)
- Fix copies for DBRX - neuron fix (30610)

Thanks michaelbenayoun !

4.40.1

Kudos to pcuenca for the prompt fix in: 

- Make EosTokenCriteria compatible with mps 30376  

To support `EosTokenCriteria`  on MPS while `pytorch` adds this functionality.

4.40.0

New model additions

Llama 3 

Llama 3 is supported in this release through the Llama 2 architecture and some fixes in the `tokenizers` library.

Idefics2

<img src="https://huggingface.co/HuggingFaceM4/idefics-80b/resolve/main/assets/IDEFICS.png"
alt="drawing" width="300"/>

The Idefics2 model was created by the Hugging Face M4 team and authored by Léo Tronchon, Hugo Laurencon, Victor Sanh. The accompanying blog post can be found here.

Idefics2 is an open multimodal model that accepts arbitrary sequences of image and text inputs and produces text outputs. The model can answer questions about images, describe visual content, create stories grounded on multiple images, or simply behave as a pure language model without visual inputs. It improves upon IDEFICS-1, notably on document understanding, OCR, or visual reasoning. Idefics2 is lightweight (8 billion parameters) and treats images in their native aspect ratio and resolution, which allows for varying inference efficiency.

* Add Idefics2  by amyeroberts in 30253

Recurrent Gemma

<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/recurrent-gemma.png"
alt="drawing" width="600"/>

<small> Recurrent Gemma architecture. Taken from the <a href="https://arxiv.org/pdf/2402.19427.pdf">original paper.</a> </small>

The Recurrent Gemma model was proposed in RecurrentGemma: Moving Past Transformers for Efficient Open Language Models by the Griffin, RLHF and Gemma Teams of Google.

The abstract from the paper is the following:

We introduce RecurrentGemma, an open language model which uses Google’s novel Griffin architecture. Griffin combines linear recurrences with local attention to achieve excellent performance on language. It has a fixed-sized state, which reduces memory use and enables efficient inference on long sequences. We provide a pre-trained model with 2B non-embedding parameters, and an instruction tuned variant. Both models achieve comparable performance to Gemma-2B despite being trained on fewer tokens.

* Add recurrent gemma  by ArthurZucker in 30143

Jamba

Jamba is a pretrained, mixture-of-experts (MoE) generative text model, with 12B active parameters and an overall of 52B parameters across all experts. It supports a 256K context length, and can fit up to 140K tokens on a single 80GB GPU.

As depicted in the diagram below, Jamba’s architecture features a blocks-and-layers approach that allows Jamba to successfully integrate Transformer and Mamba architectures altogether. Each Jamba block contains either an attention or a Mamba layer, followed by a multi-layer perceptron (MLP), producing an overall ratio of one Transformer layer out of every eight total layers.

![image](https://github.com/huggingface/transformers/assets/48595927/d78bb917-7a8a-4959-8206-e493c6c75f3d)

Jamba introduces the first `HybridCache` object that allows it to natively support assisted generation, contrastive search, speculative decoding, beam search and all of the awesome features from the `generate` API! 

* Add jamba  by tomeras91 in 29943

DBRX

DBRX is a [transformer-based](https://www.isattentionallyouneed.com/) decoder-only large language model (LLM) that was trained using next-token prediction. It uses a *fine-grained* mixture-of-experts (MoE) architecture with 132B total parameters of which 36B parameters are active on any input.

It was pre-trained on 12T tokens of text and code data. Compared to other open MoE models like Mixtral-8x7B and Grok-1, DBRX is fine-grained, meaning it uses a larger number of smaller experts. DBRX has 16 experts and chooses 4, while Mixtral-8x7B and Grok-1 have 8 experts and choose 2.

This provides 65x more possible combinations of experts and the authors found that this improves model quality. DBRX uses rotary position encodings (RoPE), gated linear units (GLU), and grouped query attention (GQA).

* Add DBRX Model  by abhi-mosaic in 29921

OLMo

The OLMo model was proposed in OLMo: Accelerating the Science of Language Models by Dirk Groeneveld, Iz Beltagy, Pete Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Harsh Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Raghavi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, Will Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah A. Smith, Hannaneh Hajishirzi.

OLMo is a series of Open Language Models designed to enable the science of language models. The OLMo models are trained on the Dolma dataset. We release all code, checkpoints, logs (coming soon), and details involved in training these models.

* Add OLMo model family  by 2015aroras in 29890

Qwen2MoE

Qwen2MoE is the new model series of large language models from the Qwen team. Previously, we released the Qwen series, including Qwen-72B, Qwen-1.8B, Qwen-VL, Qwen-Audio, etc.

Model Details
Qwen2MoE is a language model series including decoder language models of different model sizes. For each size, we release the base language model and the aligned chat model. Qwen2MoE has the following architectural choices:

Qwen2MoE is based on the Transformer architecture with SwiGLU activation, attention QKV bias, group query attention, mixture of sliding window attention and full attention, etc. Additionally, we have an improved tokenizer adaptive to multiple natural languages and codes.
Qwen2MoE employs Mixture of Experts (MoE) architecture, where the models are upcycled from dense language models. For instance, Qwen1.5-MoE-A2.7B is upcycled from Qwen-1.8B. It has 14.3B parameters in total and 2.7B activated parameters during runtime, while it achieves comparable performance with Qwen1.5-7B, with only 25% of the training resources.

* Add Qwen2MoE  by bozheng-hit in 29377

Grounding Dino

<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/grouding_dino_architecture.png"
alt="drawing" width="600"/>

<small> Taken from the <a href="https://arxiv.org/pdf/2303.05499.pdf">original paper.</a> </small>

The Grounding DINO model was proposed in Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection by Shilong Liu, Zhaoyang Zeng, Tianhe Ren, Feng Li, Hao Zhang, Jie Yang, Chunyuan Li, Jianwei Yang, Hang Su, Jun Zhu, Lei Zhang. Grounding DINO extends a closed-set object detection model with a text encoder, enabling open-set object detection. The model achieves remarkable results, such as 52.5 AP on COCO zero-shot.

* Adding grounding dino  by EduardoPach in 26087

Static pretrained maps

Static pretrained maps have been removed from the library's internals and are currently deprecated. These used to reflect all the available checkpoints for a given architecture on the Hugging Face Hub, but their presence does not make sense in light of the huge growth of checkpoint shared by the community.

With the objective of lowering the bar of model contributions and reviewing, we first start by removing legacy objects such as this one which do not serve a purpose.

* Remove static pretrained maps from the library's internals  by LysandreJik in 29112

Notable improvements

Processors improvements

Processors are ungoing changes in order to uniformize them and make them clearer to use. 

* Separate out kwargs in processor  by amyeroberts in 30193
* [Processor classes] Update docs  by NielsRogge in 29698

SDPA
* re-introduced the fast path for sdpa by fxmarty  in 30070


Push to Hub for pipelines

Pipelines can now be pushed to Hub using a convenient `push_to_hub` method.

* add `push_to_hub` to pipeline  by not-lain in 29172

Flash Attention 2 for more models (M2M100, NLLB, GPT2, MusicGen) !

Thanks to the community contribution, Flash Attention 2 has been integrated for more architectures

* Adding Flash Attention 2 Support for GPT2  by EduardoPach in 29226
* Add Flash Attention 2 support to Musicgen and Musicgen Melody  by ylacombe in 29939
* Add Flash Attention 2 to M2M100 model  by visheratin in 30256

Improvements and bugfixes

* [docs] Remove redundant `-`  and `the` from custom_tools.md  by windsonsea in 29767
* Fixed typo in quantization_config.py  by kurokiasahi222 in 29766
* OWL-ViT box_predictor inefficiency issue  by RVV-karma in 29712
* Allow `-OO` mode for `docstring_decorator`  by matthid in 29689
* fix issue with logit processor during beam search in Flax  by giganttheo in 29636
* Fix docker image build for `Latest PyTorch + TensorFlow [dev]`  by ydshieh in 29764
* [`LlavaNext`] Fix llava next unsafe imports  by ArthurZucker in 29773
* Cast bfloat16 to float32 for Numpy conversions  by Rocketknight1 in 29755
* Silence deprecations and use the DataLoaderConfig  by muellerzr in 29779
* Add deterministic config to `set_seed`  by muellerzr in 29778
* Add support for `torch_dtype` in the run_mlm example  by jla524 in 29776
* Generate: remove legacy generation mixin imports  by gante in 29782
* Llama: always convert the causal mask in the SDPA code path  by gante in 29663
* Prepend `bos token` to Blip generations  by zucchini-nlp in 29642
* Change in-place operations to out-of-place in LogitsProcessors  by zucchini-nlp in 29680
* [`quality`] update quality check to make sure we check imports 😈   by ArthurZucker in 29771
* Fix type hint for train_dataset param of Trainer.__init__() to allow IterableDataset.  Issue 29678  by stevemadere in 29738
* Enable AMD docker build CI  by IlyasMoutawwakil in 29803
* Correct llava mask & fix missing setter for `vocab_size`  by fxmarty in 29389
* rm input dtype change in CPU  by jiqing-feng in 28631
* Generate: remove unused attributes in `AssistedCandidateGenerator`  by gante in 29787
* replaced concatenation to f-strings to improve readability and unify …  by igeni in 29785
* [`cleanup`] vestiges of causal mask  by ArthurZucker in 29806
* Complete security policy with mentions of remote code  by LysandreJik in 29707
* [`SuperPoint`] Fix doc example  by amyeroberts in 29816
* [DOCS] Fix typo for llava next docs  by aliencaocao in 29829
* model_summary.md - Restore link to Harvard's Annotated Transformer.  by gamepad-coder in 29702
* Fix the behavior of collecting 'num_input_tokens_seen'  by YouliangHUANG in 29099
* Populate torch_dtype from model to pipeline  by B-Step62 in 28940
* remove quotes in code example  by johko in 29812
* Add warnings if training args differ from checkpoint trainer state  by jonflynng in 29255
* Replace 'decord' with 'av' in VideoClassificationPipeline  by Tyx-main in 29747
* Fix header in IFE task guide  by merveenoyan in 29859
* [docs] Indent ordered list in add_new_model.md  by windsonsea in 29796
* Allow `bos_token_id is None` during the generation with `inputs_embeds`  by LZHgrla in 29772
* Add `cosine_with_min_lr` scheduler in Trainer  by liuyanyi in 29341
* Disable AMD memory benchmarks  by IlyasMoutawwakil in 29871
* Set custom_container in build docs workflows  by Wauplin in 29855
* Support `num_attention_heads` != `num_key_value_heads` in Flax Llama Implementation  by bminixhofer in 29557
* Mamba `slow_forward` gradient fix  by vasqu in 29563
* Fix 29807, sinusoidal positional encodings overwritten by post_init()  by hovnatan in 29813
* Reimplement "Automatic safetensors conversion when lacking these files"  by LysandreJik in 29846
* fix fuyu device_map compatibility  by SunMarc in 29880
* Move `eos_token_id` to stopping criteria  by zucchini-nlp in 29459
* add Cambricon MLUs support  by huismiling in 29627
* MixtralSparseMoeBlock: add gate jitter  by lorenzoverardo in 29865
* Fix typo in T5Block error message  by Mingosnake in 29881
* [`make fix-copies`] update and help  by ArthurZucker in 29924
* [`GptNeox`] don't gather on pkv when using the trainer  by ArthurZucker in 29892
* [`pipeline`]. Zero shot add doc warning  by ArthurZucker in 29845
* [doc] fix some typos and add `xpu` to the testing documentation  by faaany in 29894
* Tests: replace `torch.testing.assert_allclose` by `torch.testing.assert_close`  by gante in 29915
* Add beam search visualizer to the doc  by aymeric-roucher in 29876
* Safe import of LRScheduler  by amyeroberts in 29919
* add functions to inspect model and optimizer status to trainer.py  by CKeibel in 29838
* RoPE models: add numerical sanity-check test for RoPE scaling  by gante in 29808
* [`Mamba`] from pretrained issue with `self.embeddings`  by ArthurZucker in 29851
* [ `TokenizationLlama`] fix the way we convert tokens to strings to keep leading spaces 🚨 breaking fix  by ArthurZucker in 29453
* Allow GradientAccumulationPlugin to be configured from AcceleratorConfig  by fabianlim in 29589
* [`BC`] Fix BC for other libraries  by ArthurZucker in 29934
* Fix doc issue 29758 in DebertaV2Config class  by vinayakkgarg in 29842
* [`LlamaSlowConverter`] Slow to Fast better support  by ArthurZucker in 29797
* Update installs in image classification doc  by MariaHei in 29947
* [`StableLm`] Add QK normalization and Parallel Residual Support  by jon-tow in 29745
* Mark `test_eager_matches_sdpa_generate` flaky for some models  by ydshieh in 29479
* Super tiny fix 12 typos about "with with"  by fzyzcjy in 29926
* Fix rope theta for OpenLlama  by jla524 in 29893
* Add warning message for `run_qa.py`  by jla524 in 29867
* fix: get mlflow version from mlflow-skinny  by clumsy in 29918
* Reset alarm signal when the function is ended  by coldnight in 29706
* Update model card and link of blog post.  by bozheng-hit in 29928
* [`BC`] Fix BC for AWQ quant  by TechxGenus in 29965
* Rework tests to compare trainer checkpoint args  by muellerzr in 29883
* Fix FA2 tests  by ylacombe in 29909
* Fix copies main ci  by ArthurZucker in 29979
* [tests] fix the wrong output in `ImageToTextPipelineTests.test_conditional_generation_llava`  by faaany in 29975
* Generate: move misplaced test  by gante in 29902
* [docs] Big model loading  by stevhliu in 29920
* [`generate`] fix breaking change for patch  by ArthurZucker in 29976
* Fix 29807 sinusoidal positional encodings in Flaubert, Informer and XLM  by hovnatan in 29904
* [bnb] Fix bug in `_replace_with_bnb_linear`  by SunMarc in 29958
* Adding FlaxNoRepeatNGramLogitsProcessor  by giganttheo in 29677
* [Docs] Make an ordered list prettier in add_tensorflow_model.md  by windsonsea in 29949
* Fix `skip_special_tokens` for `Wav2Vec2CTCTokenizer._decode`  by msublee in 29311
* Hard error when ignoring tensors.  by Narsil in 27484) 
* Generate: fix logits processors doctests  by gante in 29718
* Fix `remove_columns` in `text-classification` example  by mariosasko in 29351
* Update `tests/utils/tiny_model_summary.json`  by ydshieh in 29941
* Make EncodecModel.decode ONNX exportable  by fxmarty in 29913
* Fix Swinv2ForImageClassification NaN output  by miguelm-almeida in 29981
* Fix Qwen2Tokenizer  by jklj077 in 29929
* Fix `kwargs` handling in `generate_with_fallback`  by cifkao in 29225
* Fix probability computation in `WhisperNoSpeechDetection` when recomputing scores  by cifkao in 29248
* Fix vipllava for generation  by zucchini-nlp in 29874
* [docs] Fix audio file  by stevhliu in 30006
* Superpoint imports fix  by zucchini-nlp in 29898
* [`Main CIs`] Fix the red cis   by ArthurZucker in 30022
* Make clearer about zero_init requirements  by muellerzr in 29879
* Enable multi-device for efficientnet  by jla524 in 29989
* Add a converter from mamba_ssm -> huggingface mamba  by byi8220 in 29705
* [`ProcessingIdefics`] Attention mask bug with padding  by byi8220 in 29449
* Add `whisper` to `IMPORTANT_MODELS`  by ydshieh in 30046
* skip `test_encode_decode_fast_slow_all_tokens` for now  by ydshieh in 30044
* if output is tuple like facebook/hf-seamless-m4t-medium, waveform is …  by sywangyi in 29722
* Fix mixtral ONNX Exporter Issue.  by AdamLouly in 29858
* [Trainer] Allow passing image processor  by NielsRogge in 29896
* [bnb] Fix offload test  by SunMarc in 30039
* Update quantizer_bnb_4bit.py: In the ValueError string there should be "....you need to set `llm_int8_enable_fp32_cpu_offload=True`...." instead of "`load_in_8bit_fp32_cpu_offload=True`".  by miRx923 in 30013
* [test fetcher] Always include the directly related test files  by ydshieh in 30050
* Fix `torch.fx` symbolic tracing for LLama  by michaelbenayoun in 30047
* Refactor daily CI workflow  by ydshieh in 30012
* Add docstrings and types for MambaCache  by koayon in 30023
* Fix auto tests  by ydshieh in 30067
* Fix whisper kwargs and generation config  by zucchini-nlp in 30018
* doc: Correct spelling mistake  by caiyili in 30107
* [Whisper] Computing features on GPU in batch mode for whisper feature extractor.     by vaibhavagg303 in 29900
* Change log level to warning for num_train_epochs override  by xu-song in 30014
* Make MLFlow version detection more robust and handles mlflow-skinny  by helloworld1 in 29957
* updated examples/pytorch/language-modeling scripts and requirements.txt to require datasets>=2.14.0  by Patchwork53 in 30120
* [tests] add `require_bitsandbytes` marker  by faaany in 30116
* fixing issue 30034 - adding data format for run_ner.py  by JINO-ROHIT in 30088
* Patch fix - don't use safetensors for TF models  by amyeroberts in 30118
* [29174] ImportError Fix: Trainer with PyTorch requires accelerate>=0.20.1 Fix  by UtkarshaGupte in 29888
* Accept token in trainer.push_to_hub()  by mapmeld in 30093
* fix learning rate display in trainer when using galore optimizer  by vasqu in 30085
* Fix falcon with SDPA, alibi but no passed mask  by fxmarty in 30123
* Trainer / Core : Do not change init signature order  by younesbelkada in 30126
* Make vitdet jit trace complient  by fxmarty in 30065
* Fix typo at ImportError  by DrAnaximandre in 30090
* Adding `mps` as device for `Pipeline` class  by fnhirwa in 30080
* Fix failing DeepSpeed model zoo tests  by pacman100 in 30112
* Add datasets.Dataset to Trainer's train_dataset and eval_dataset type hints  by ringohoffman in 30077
* Fix docs Pop2Piano  by zucchini-nlp in 30140
* Revert workaround for TF safetensors loading  by Rocketknight1 in 30128
* [Trainer] Fix default data collator  by NielsRogge in 30142
* [Trainer] Undo 29896  by NielsRogge in 30129
* Fix slow tests for important models to be compatible with A10 runners  by ydshieh in 29905
* Send headers when converting safetensors  by ydshieh in 30144
* Fix quantization tests  by SunMarc in 29914
* [docs] Fix image segmentation guide  by stevhliu in 30132
* [CI] Fix setup  by SunMarc in 30147
* Fix length related warnings in speculative decoding  by zucchini-nlp in 29585
* Fix and simplify semantic-segmentation example  by qubvel in 30145
* [CI] Quantization workflow fix  by SunMarc in 30158
* [tests] make 2 tests device-agnostic   by faaany in 30008
* Add str to TrainingArguments report_to type hint  by ringohoffman in 30078
* [UDOP] Fix tests  by NielsRogge in 29573
* [UDOP] Improve docs, add resources  by NielsRogge in 29571
* Fix accelerate kwargs for versions <0.28.0  by vasqu in 30086
* Fix typing annotation in hf_argparser  by xu-song in 30156
* Fixing a bug when MlFlow try to log a torch.tensor  by etiennebonnafoux in 29932
* Fix natten install in docker  by ydshieh in 30161
* FIX / bnb: fix torch compatiblity issue with `itemize`  by younesbelkada in 30162
* Update config class check in auto factory  by Rocketknight1 in 29854
* Fixed typo in comments/documentation for Pipelines documentation  by DamonGuzman in 30170
* Fix Llava chat template examples  by lewtun in 30130
* Guard XLA version imports  by muellerzr in 30167
* chore: remove repetitive words  by hugehope in 30174
* fix: Fixed `ruff` configuration to avoid deprecated configuration warning  by Sai-Suraj-27 in 30179
* Refactor Cohere Model  by saurabhdash2512 in 30027
* Update output of SuperPointForKeypointDetection  by NielsRogge in 29809
* Falcon: make activation, ffn_hidden_size configurable  by sshleifer in 30134
* Docs PR template  by stevhliu in 30171
* ENH: [`CI`] Add new workflow to run slow tests of important models on push main if they are modified  by younesbelkada in 29235
* Fix pipeline logger.warning_once bug  by amyeroberts in 30195
* fix: Replaced deprecated `logger.warn` with `logger.warning`  by Sai-Suraj-27 in 30197
* fix typo  by mdeff in 30220
* fix fuyu doctest  by molbap in 30215
* Fix `RecurrentGemmaIntegrationTest.test_2b_sample`  by ydshieh in 30222
* Update modeling_bark.py  by bes-dev in 30221
* Fix/Update for doctest  by ydshieh in 30216
* Fixed config.json download to go to user-supplied cache directory  by ulatekh in 30189
* Add test for parse_json_file and change typing to os.PathLike  by xu-song in 30183
* fix: Replace deprecated `assertEquals` with `assertEqual`  by Sai-Suraj-27 in 30241
* Set pad_token in run_glue_no_trainer.py 28534  by JINO-ROHIT in 30234
* fix: Replaced deprecated `typing.Text`  with `str`  by Sai-Suraj-27 in 30230
* Refactor doctest  by ydshieh in 30210
* fix: Fixed `type annotation` for compatability with python 3.8  by Sai-Suraj-27 in 30243
* Fix doctest more (for `docs/source/en`)  by ydshieh in 30247
* round epoch only in console  by xdedss in 30237
* update github actions packages' version to suppress warnings  by ydshieh in 30249
* [tests] add the missing `require_torch_multi_gpu` flag  by faaany in 30250
* [Docs] Update recurrent_gemma.md for some minor nits  by sayakpaul in 30238
* Remove incorrect arg in codellama doctest  by Rocketknight1 in 30257
* Update `ko/_toctree.yml`   by jungnerd in 30062
* More fixes for doctest  by ydshieh in 30265
* FIX: Fix corner-case issue with the important models workflow  by younesbelkada in 30212
* FIX: Fix 8-bit serialization tests  by younesbelkada in 30051
* Allow for str versions of dicts based on typing  by muellerzr in 30227
* Workflow: Update tailscale to release version  by younesbelkada in 30268
* Raise relevent err when wrong type is passed in as the accelerator_config  by muellerzr in 29997
* BLIP - fix pt-tf equivalence test  by amyeroberts in 30258
* fix: Fixed a `raise` statement  by Sai-Suraj-27 in 30275
* Fix test fetcher (doctest) + `Idefics2`'s doc example  by ydshieh in 30274
* Fix SDPA sliding window compatibility  by fxmarty in 30127
* Fix SpeechT5 forward docstrings  by ylacombe in 30287
* FIX / AWQ: Fix failing exllama test  by younesbelkada in 30288
* Configuring Translation Pipelines documents update 27753  by UtkarshaGupte in 29986
* Enable fx tracing for Mistral  by zucchini-nlp in 30209
* Fix test `ExamplesTests::test_run_translation`  by ydshieh in 30281
* Fix `Fatal Python error: Bus error` in `ZeroShotAudioClassificationPipelineTests`  by ydshieh in 30283
* FIX: Fix push important models CI  by younesbelkada in 30291
* Add token type ids to CodeGenTokenizer  by st81 in 29265
* Add strategy to store results in evaluation loop  by qubvel in 30267
* Upgrading to tokenizers 0.19.0  by Narsil in 30289
* Re-enable SDPA's FA2 path  by fxmarty in 30070
* Fix quality Olmo + SDPA  by fxmarty in 30302
* Fix donut token2json multiline  by qubvel in 30300
* Fix all torch pipeline failures except one  by ydshieh in 30290
* Add atol for sliding window test  by fxmarty in 30303
* Fix RecurrentGemma device_map  by SunMarc in 30273
* Revert "Re-enable SDPA's FA2 path  by ArthurZucker in 30070)" 
* Do not drop mask with SDPA for more cases  by fxmarty in 30311
* FIX: Fixes unexpected behaviour for Llava / LLama & AWQ Fused modules + revert 30070 at the same time  by younesbelkada in 30317

Significant community contributions

The following contributors have made significant changes to the library over the last release:

* bozheng-hit
 * Add Qwen2MoE (29377)
 * Update model card and link of blog post. (29928)
* EduardoPach
 * Adding Flash Attention 2 Support for GPT2 (29226)
 * Adding grounding dino (26087)
* 2015aroras
 * Add OLMo model family (29890)
* tomeras91
 * Add jamba (29943)
* abhi-mosaic
 * Add DBRX Model (29921)

Links

• PyPI: https://pypi.org/project/transformers
• Changelog: https://data.safetycli.com/changelogs/transformers/
• Repo: https://github.com/huggingface/transformers

[pyup-bot]

Closing this in favor of #250