transformers 4.35.0

Safetensors serialization by default, DistilWhisper, Fuyu, Kosmos-2, SeamlessM4T, Owl-v2

on Python PyPI

New models

Distil-Whisper

Distil-Whisper is a distilled version of Whisper that is 6 times faster, 49% smaller, and performs within 1% word error rate (WER) on out-of-distribution data. It was proposed in the paper Robust Knowledge Distillation via Large-Scale Pseudo Labelling.

Distil-Whisper copies the entire encoder from Whisper, meaning it retains Whisper's robustness to different audio conditions. It only copies 2 decoder layers, which significantly reduces the time taken to auto-regressively generate text tokens:

Distil-Whisper is MIT licensed and directly available in the Transformers library with chunked long-form inference, Flash Attention 2 support, and Speculative Decoding. For details on using the model, refer to the following instructions.

Joint work from @sanchit-gandhi, @patrickvonplaten and @srush.

• [Assistant Generation] Improve Encoder Decoder by @patrickvonplaten in #26701
• [WhisperForCausalLM] Add WhisperForCausalLM for speculative decoding by @patrickvonplaten in #27195
• [Whisper, Bart, MBart] Add Flash Attention 2 by @patrickvonplaten in #27203

Fuyu

The Fuyu model was created by ADEPT, and authored by Rohan Bavishi, Erich Elsen, Curtis Hawthorne, Maxwell Nye, Augustus Odena, Arushi Somani, Sağnak Taşırlar.

The authors introduced Fuyu-8B, a decoder-only multimodal model based on the classic transformers architecture, with query and key normalization. A linear encoder is added to create multimodal embeddings from image inputs.

By treating image tokens like text tokens and using a special image-newline character, the model knows when an image line ends. Image positional embeddings are removed. This avoids the need for different training phases for various image resolutions. With 8 billion parameters and licensed under CC-BY-NC, Fuyu-8B is notable for its ability to handle both text and images, its impressive context size of 16K, and its overall performance.

Joint work from @molbap, @pcuenca, @amyeroberts, @ArthurZucker

• Add fuyu model by @molbap in #26911
• Fuyu: improve image processing by @molbap in #27007

SeamlessM4T

The SeamlessM4T model was proposed in SeamlessM4T — Massively Multilingual & Multimodal Machine Translation by the Seamless Communication team from Meta AI.

SeamlessM4T is a collection of models designed to provide high quality translation, allowing people from different linguistic communities to communicate effortlessly through speech and text.

SeamlessM4T enables multiple tasks without relying on separate models:

• Speech-to-speech translation (S2ST)
• Speech-to-text translation (S2TT)
• Text-to-speech translation (T2ST)
• Text-to-text translation (T2TT)
• Automatic speech recognition (ASR)

SeamlessM4TModel can perform all the above tasks, but each task also has its own dedicated sub-model.

• Add Seamless M4T model by @ylacombe in #25693

Kosmos-2

The KOSMOS-2 model was proposed in Kosmos-2: Grounding Multimodal Large Language Models to the World by Zhiliang Peng, Wenhui Wang, Li Dong, Yaru Hao, Shaohan Huang, Shuming Ma, Furu Wei.

KOSMOS-2 is a Transformer-based causal language model and is trained using the next-word prediction task on a web-scale dataset of grounded image-text pairs GRIT. The spatial coordinates of the bounding boxes in the dataset are converted to a sequence of location tokens, which are appended to their respective entity text spans (for example, a snowman followed by <patch_index_0044><patch_index_0863>). The data format is similar to “hyperlinks” that connect the object regions in an image to their text span in the corresponding caption.

• Add Kosmos-2 model by @ydshieh in #24709

Owl-v2

OWLv2 was proposed in Scaling Open-Vocabulary Object Detection by Matthias Minderer, Alexey Gritsenko, Neil Houlsby. OWLv2 scales up OWL-ViT using self-training, which uses an existing detector to generate pseudo-box annotations on image-text pairs. This results in large gains over the previous state-of-the-art for zero-shot object detection.

• Add OWLv2, bis by @NielsRogge in #26668

🚨🚨🚨 Safetensors by default for torch serialization 🚨🚨🚨

Version v4.35.0 now puts safetensors serialization by default. This is a significant change targeted at making users of the Hugging Face Hub, transformers, and any downstream library leveraging it safer.

The safetensors library is a safe serialization framework for machine learning tensors. It has been audited and will become the default serialization framework for several organizations (Hugging Face, EleutherAI, Stability AI).

It was already the default loading mechanism since v4.30.0 and would therefore already default to loading model.safetensors files instead of pytorch_model.bin if these were present in the repository.

With v4.35.0, any call to save_pretrained for torch models will now save a safetensors file. This safetensors file is in the PyTorch format, but can be loaded in TensorFlow and Flax models alike.

⚠️ If you run into any issues with this, please let us know ASAP in the issues so that we may help you. Namely, the following errors may indicate something is up:

• Loading a safetensors file and having a warning mentioning missing weights unexpectedly
• Obtaining completely wrong/random results at inference after loading a pretrained model that you have saved in safetensors

If you wish to continue saving files in the .bin format, you can do so by specifying safe_serialization=False in all your save_pretrained calls.

• Safetensors serialization by default by @LysandreJik in #27064

Chat templates

Chat templates have been expanded with the addition of the add_generation_prompt argument to apply_chat_template(). This has also enabled us to rework the ConversationalPipeline class to use chat templates. Any model with a chat template is now automatically usable through ConversationalPipeline.

• Add add_generation_prompt argument to apply_chat_template by @Rocketknight1 in #26573
• Conversation pipeline fixes by @Rocketknight1 in #26795

Guides

Two new guides on LLMs were added the library:

• [docs] LLM prompting guide by @MKhalusova in #26274
• [docs] Optimizing LLMs by @patrickvonplaten in #26058

Quantization

Exllama-v2 integration

Exllama-v2 provides better GPTQ kernel for higher throughput and lower latency for GPTQ models. The original code can be found here.

• add exllamav2 arg by @SunMarc in #26437
• Add exllamav2 better by @SunMarc in #27111

You will need the latest versions of optimum and auto-gptq. Read more about the integration here.

AWQ integration

AWQ is a new and popular quantization scheme, already used in various libraries such as TGI, vllm, etc. and known to be faster than GPTQ models according to some benchmarks. The original code can be found here and here you can read more about the original paper.

We support AWQ inference with original kernels as well as kernels provided through autoawq package that you can simply install with pip install autoawq.

• [core / Quantization ] AWQ integration by @younesbelkada in #27045

We also provide an example script on how to push quantized weights on the hub on the original repository.

Read more about the benchmarks and the integration here

GPTQ on CPU !

You can now run GPTQ models on CPU using the latest version of auto-gptq thanks to @vivekkhandelwal1 !

• Add support for loading GPTQ models on CPU by @vivekkhandelwal1 in #26719

Attention mask refactor

We refactored the attention mask logic for major models in transformers. For instance, we removed padding_mask argument which was ambiguous for some users

• Remove ambiguous padding_mask and instead use a 2D->4D Attn Mask Mapper by @patrickvonplaten in #26792
• [Attention Mask] Refactor all encoder-decoder attention mask by @patrickvonplaten in #27086

Flash Attention 2 for more models + quantization fine-tuning bug fix

Gpt-bigcode (starcoder), whisper, Bart and MBart now supports FA-2 ! Use it by simply passing use_flash_attention_2=True to from_pretrained. Some bugfixes with respect to mixed precision training with FA2 have been also addressed.

• Add flash attention for gpt_bigcode by @susnato in #26479
• [FA2] Fix flash attention 2 fine-tuning with Falcon by @younesbelkada in #26852
• [Whisper, Bart, MBart] Add Flash Attention 2 by @patrickvonplaten in #27203

A bugfix with respect to fine-tuning with FA-2 in bfloat16 was addressed. You should now smoothly fine-tune FA-2 models in bfloat16 using quantized base models.

• 🚨🚨🚨 [Quantization] Store the original dtype in the config as a private attribute 🚨🚨🚨 by @younesbelkada in #26761
• [FA-2] Final fix for FA2 dtype by @younesbelkada in #26846

Neftune

NEFTune is a new technique to boost Supervised Fine-tuning performance by adding random noise on the embedding vector. Read more about it on the original paper here

We propose a very simple API for users to benefit from this technique, simply pass a valid neftune_noise_alpha parameter to TrainingArguments

Read more about the API here

• [FEAT] Add Neftune into transformers Trainer by @younesbelkada in #27141

Gradient checkpointing refactor

We have refactored the gradient checkpointing API so that users can pass keyword arguments supported by torch.utils.checkpoint.checkpoint directly through gradient_checkpointing_kwargs when calling gradient_checkpointing_enable(), e.g.

from transformers import AutoModelForCausalLM

model = AutoModelForCausalLM.from_pretrained("facebook/opt-125m")
model.gradient_checkpointing_enable(gradient_checkpointing_kwargs={"use_reentrant": False})

gradient_checkpointing_kwargs is also supported with Trainer through TrainingArguments.

• [Trainer / GC] Add gradient_checkpointing_kwargs in trainer and training arguments by @younesbelkada in #27068
• [core] Refactor of gradient_checkpointing by @younesbelkada in #27020
• [core/ GC / tests] Stronger GC tests by @younesbelkada in #27124
• Fix import of torch.utils.checkpoint by @NielsRogge in #27155

The refactor should be totally backward compatible with previous behaviour. For superusers, you can still use the attribute gradient_checkpointing on model's submodules to control the activation / deactivation of gradient_checkpointing.

Breaking changes

• 🚨🚨🚨 [Quantization] Store the original dtype in the config as a private attribute 🚨🚨🚨 by @younesbelkada in #26761
• 🚨🚨 Generate: change order of ops in beam sample to avoid nans by @gante in #26843
• 🚨🚨 Raise error when no speaker embeddings in speecht5._generate_speech by @ylacombe in #26418

Bugfixes and improvements

• [Nougat] from transformers import * by @ArthurZucker in #26562
• [Whisper] Allow basic text normalization by @sanchit-gandhi in #26149
• 🌐 [i18n-KO] Translated semantic_segmentation.md to Korean by @jungnerd in #26515
• [Tokenizers] Skip tests temporarily by @LysandreJik in #26574
• docs: feat: add clip notebook resources from OSSCA community by @junejae in #26505
• Extend Trainer to enable Ascend NPU to use the fused Adamw optimizer when training by @statelesshz in #26194
• feat: add trainer label to wandb run upon initialization by @parambharat in #26466
• Docstring check by @sgugger in #26052
• refactor: change default block_size by @pphuc25 in #26229
• [Mistral] Update config docstring by @sanchit-gandhi in #26593
• Add # Copied from statements to audio feature extractors that use the floats_list function by @dg845 in #26581
• Fix embarrassing typo in the doc chat template! by @Rocketknight1 in #26596
• Fix encoder->decoder typo bug in convert_t5x_checkpoint_to_pytorch.py by @soyoung97 in #26587
• skip flaky hub tests by @ArthurZucker in #26594
• Update mistral.md to update 404 link by @Galland in #26590
• [Wav2Vec2] Fix tokenizer set lang by @sanchit-gandhi in #26349
• add zh translation for installation by @yyLeaves in #26084
• [ NougatProcessor] Fix the default channel by @ArthurZucker in #26608
• [GPTNeoX] Faster rotary embedding for GPTNeoX (based on llama changes) by @ArthurZucker in #25830
• [Falcon] Set use_cache=False before creating presents which relies on use_cache by @yundai424 in #26328
• Fix failing tests on main due to torch 2.1 by @ydshieh in #26607
• Make ModelOutput serializable by @cbensimon in #26493
• [core] fix silent bug keep_in_fp32 modules by @younesbelkada in #26589
• #26566 swin2 sr allow in out channels by @marvingabler in #26568
• Don't close ClearML task if it was created externally by @eugen-ajechiloae-clearml in #26614
• Fix transformers-pytorch-gpu docker build by @ydshieh in #26615
• [docs] Update to scripts building index.md by @MKhalusova in #26546
• Don't install pytorch-quantization in Doc Builder docker file by @ydshieh in #26622
• Remove unnecessary views of position_ids by @ramiro050 in #26059
• Fixed inconsistency in several fast tokenizers by @Towdo in #26561
• Update tokenization_code_llama_fast.py by @andyl98 in #26576
• Remove unnecessary unsqueeze - squeeze in rotary positional embedding by @fxmarty in #26162
• Update chat template docs with more tips on writing a template by @Rocketknight1 in #26625
• fix RoPE t range issue for fp16 by @rui-ren in #26602
• Fix failing MusicgenTest .test_pipeline_text_to_audio by @ydshieh in #26586
• remove SharedDDP as it is deprecated by @statelesshz in #25702
• [LlamaTokenizerFast] Adds edge cases for the template processor by @ArthurZucker in #26606
• [docstring] Fix docstring for AlbertConfig by @ydshieh in #26636
• docs(zh): review and punctuation & space fix by @wfjsw in #26627
• [DINOv2] Convert more checkpoints by @NielsRogge in #26177
• Fixed malapropism error by @Zhreyu in #26660
• fix links in README.md for the GPT, GPT-2, and Llama2 Models by @dcarpintero in #26640
• Avoid CI OOM by @ydshieh in #26639
• fix typos in idefics.md by @dribnet in #26648
• [docstring] Fix docstring CLIP configs by @isaac-chung in #26677
• [docstring] Fix docstring for CLIPImageProcessor by @isaac-chung in #26676
• [docstring] Fix docstring for DonutImageProcessor by @abzdel in #26641
• Fix stale bot by @LysandreJik in #26692
• [docstring] Fix docstrings for CLIP by @isaac-chung in #26691
• Control first downsample stride in ResNet by @jiqing-feng in #26374
• Fix Typo: table in deepspeed.md by @Pairshoe in #26705
• [docstring] Fix docstring for LlamaConfig by @pavaris-pm in #26685
• fix a typo in flax T5 attention - attention_mask variable is misnamed by @giganttheo in #26663
• Fix source_prefix default value by @jheitmann in #26654
• [JAX] Replace uses of jnp.array in types with jnp.ndarray. by @hvaara in #26703
• Make Whisper Encoder's sinusoidal PE non-trainable by default by @gau-nernst in #26032
• In assisted decoding, pass model_kwargs to model's forward call (fix prepare_input_for_generation in all models) by @sinking-point in #25242
• Update docs to explain disabling callbacks using report_to by @nebrelbug in #26155
• Copied from for test files by @ydshieh in #26713
• [docstring] SwinModel docstring fix by @shivanandmn in #26679
• fix the model card issue as use_cuda_amp is no more available by @pacman100 in #26731
• Fix stale bot for locked issues by @LysandreJik in #26711
• Fix checkpoint path in no_trainer scripts by @muellerzr in #26733
• Update docker files to use torch==2.1.0 by @ydshieh in #26735
• Revert #20715 by @ydshieh in #26734
• [docstring] Fix docstring for LlamaTokenizer and LlamaTokenizerFast by @minhoryang in #26669
• [docstring] Fix docstring for CodeLlamaTokenizer by @Bojun-Feng in #26709
• add japanese documentation by @rajveer43 in #26138
• Translated the accelerate.md file of the documentation to Chinese by @liteli1987gmail in #26161
• Fix doctest for Blip2ForConditionalGeneration by @ydshieh in #26737
• Add many missing spaces in adjacent strings by @tomaarsen in #26751
• Warnings controlled by logger level by @LysandreJik in #26527
• Fix PersimmonIntegrationTest OOM by @ydshieh in #26750
• Fix MistralIntegrationTest OOM by @ydshieh in #26754
• Fix backward compatibility of Conversation by @wdhorton in #26741
• [docstring] Fix UniSpeech, UniSpeechSat, Wav2Vec2ForCTC by @gizemt in #26664
• [docstring] Update GPT2 and Whisper by @McDonnellJoseph in #26642
• [docstring] Fix docstring for 'BertGenerationConfig' by @AdwaitSalankar in #26661
• Fix PerceiverModelIntegrationTest::test_inference_masked_lm by @ydshieh in #26760
• chore: fix typos by @afuetterer in #26756
• [core] Fix fa-2 import by @younesbelkada in #26785
• Skip TrainerIntegrationFSDP::test_basic_run_with_cpu_offload if torch < 2.1 by @ydshieh in #26764
• 🌐 [i18n-KO] Translated big_models.md to Korean by @wonhyeongseo in #26245
• Update expect outputs of IdeficsProcessorTest.test_tokenizer_padding by @ydshieh in #26779
• [docstring] Fix docstring for RwkvConfig by @Bojun-Feng in #26782
• Fix num. of minimal calls to the Hub with peft for pipeline by @ydshieh in #26385
• [docstring] fix docstring DPRConfig by @AVAniketh0905 in #26674
• Disable default system prompt for LLaMA by @Rocketknight1 in #26765
• Fix Falcon generation test by @Rocketknight1 in #26770
• Fixed KeyError for Mistral by @MatteoRaso in #26682
• [Flava] Fix flava doc by @younesbelkada in #26789
• Add CLIP resources by @eenzeenee in #26534
• translation brazilian portuguese by @alvarorichard in #26769
• Fixed typos by @Zhreyu in #26810
• [docstring] Fix docstring for CanineConfig by @Sparty in #26771
• Add Japanese translation by @shinshin86 in #26799
• [docstring] Fix docstring for CodeLlamaTokenizerFast by @Bojun-Feng in #26666
• Image-to-Image Task Guide by @merveenoyan in #26595
• Make fsdp ram efficient loading optional by @pacman100 in #26631
• fix resume_from_checkpoint bug by @Jintao-Huang in #26739
• [OWL-ViT, OWLv2] Add resources by @NielsRogge in #26822
• Llama tokenizer: remove space in template comment by @pcuenca in #26788
• Better way to run AMD CI with different flavors by @ydshieh in #26634
• [docstring] Fix bert generation tokenizer by @przemL in #26820
• Conversation pipeline fixes by @Rocketknight1 in #26795
• Fix Mistral OOM again by @ydshieh in #26847
• Chore: Typo fixed in multiple files of docs/source/en/model_doc by @SusheelThapa in #26833
• fix: when window_size is passes as array by @dotneet in #26800
• Update logits_process.py docstrings to clarify penalty and reward cases (attempt #2) by @larekrow in #26784
• [docstring] Fix docstring for LukeConfig by @louietouie in #26858
• Fixed a typo in mistral.md by @DTennant in #26879*
• Translating en/internal folder docs to Japanese 🇯🇵 by @rajveer43 in #26747
• Fix TensorFlow pakage check by @jayfurmanek in #26842
• Generate: improve docstrings for custom stopping criteria by @gante in #26863
• Knowledge distillation for vision guide by @merveenoyan in #25619
• Fix Seq2seqTrainer decoder attention mask by @Rocketknight1 in #26841
• [Tokenizer] Fix slow and fast serialization by @ArthurZucker in #26570
• Emergency PR to skip conversational tests to fix CI by @Rocketknight1 in #26906
• Add default template warning by @Rocketknight1 in #26637
• Refactor code part in documentation translated to japanese by @rajveer43 in #26900
• [i18n-ZH] Translated fast_tokenizers.md to Chinese by @yyLeaves in #26910
• [FA-2] Revert suggestion that broke FA2 fine-tuning with quantized models by @younesbelkada in #26916
• [docstring] Fix docstring for ChineseCLIP by @Sparty in #26880
• [Docs] Make sure important decode and generate method are nicely displayed in Whisper docs by @patrickvonplaten in #26927
• Fix and re-enable ConversationalPipeline tests by @Rocketknight1 in #26907
• [docstring] Fix docstrings for CodeGen by @daniilgaltsev in #26821
• Fix license by @MedAymenF in #26931
• Pin Keras for now by @Rocketknight1 in #26904
• [FA-2 / Mistral] Supprot fa-2 + right padding + forward by @younesbelkada in #26912
• Generate: update basic llm tutorial by @gante in #26937
• Corrected modalities description in README_ru.md by @letohx in #26913
• [docstring] Fix docstring for speech-to-text config by @R055A in #26883
• fix set_transform link docs by @diegulio in #26856
• Fix Fuyu image scaling bug by @pcuenca in #26918
• Update README_hd.md by @biswabaibhab007 in #26872
• Added Telugu [te] translations by @hakunamatata1997 in #26828
• fix logit-to-multi-hot conversion in example by @ranchlai in #26936
• Limit to inferior fsspec version by @LysandreJik in #27010
• python falcon doc-string example typo by @SoyGema in #26995
• skip two tests by @ArthurZucker in #27013
• Nits in Llama2 docstring by @osanseviero in #26996
• Change default max_shard_size to smaller value by @younesbelkada in #26942
• [NLLB-MoE] Fix NLLB MoE 4bit inference by @younesbelkada in #27012
• [SeamlessM4T] fix copies with NLLB MoE int8 by @ArthurZucker in #27018
• small typos found by @rafaelpadilla in #26988
• Remove token_type_ids from default TF GPT-2 signature by @Rocketknight1 in #26962
• Translate pipeline_tutorial.md to chinese by @jiaqiw09 in #26954
• 🌐 [i18n-ZH] Translate multilingual into Chinese by @yyLeaves in #26935
• translate preprocessing.md to Chinese by @jiaqiw09 in #26955
• Bugfix device map detr model by @pedrogengo in #26849
• Fix little typo by @mertyyanik in #27028
• 🌐 [i18n-ZH] Translate create_a_model.md into Chinese by @yyLeaves in #27026
• Fix key dtype in GPTJ and CodeGen by @fxmarty in #26836
• Register ModelOutput as supported torch pytree nodes by @XuehaiPan in #26618
• Add default_to_square_for_size to CLIPImageProcessor by @ydshieh in #26965
• Add descriptive docstring to WhisperTimeStampLogitsProcessor by @jprivera44 in #25642
• Normalize only if needed by @mjamroz in #26049
• [TFxxxxForSequenceClassifciation] Fix the eager mode after #25085 by @ArthurZucker in #25751
• Safe import of rgb_to_id from FE modules by @amyeroberts in #27037
• add info on TRL docs by @lvwerra in #27024
• Add fuyu device map by @SunMarc in #26949
• Device agnostic testing by @vvvm23 in #25870
• Fix config silent copy in from_pretrained by @patrickvonplaten in #27043
• [docs] Performance docs refactor p.2 by @MKhalusova in #26791
• Add a default decoder_attention_mask for EncoderDecoderModel during training by @hackyon in #26752
• Fix RoPE config validation for FalconConfig + various config typos by @tomaarsen in #26929
• Skip-test by @ArthurZucker in #27062
• Fix TypicalLogitsWarper tensor OOB indexing edge case by @njhill in #26579
• [docstring] fix incorrect llama docstring: encoder -> decoder by @ztjhz in #27071
• [DOCS] minor fixes in README.md by @Akash190104 in #27048
• [docs] Add MaskGenerationPipeline in docs by @younesbelkada in #27063
• 🌐 [i18n-ZH] Translate custom_models.md into Chinese by @yyLeaves in #27065
• Hindi translation of pipeline_tutorial.md by @AaryaBalwadkar in #26837
• Handle unsharded Llama2 model types in conversion script by @coreyhu in #27069
• Bring back set_epoch for Accelerate-based dataloaders by @muellerzr in #26850
• Bumpflash_attn version to 2.1 by @younesbelkada in #27079
• Remove unneeded prints in modeling_gpt_neox.py by @younesbelkada in #27080
• Add-support for commit description by @ArthurZucker in #26704
• [Llama FA2] Re-add _expand_attention_mask and clean a couple things by @patrickvonplaten in #27074
• Correct docstrings and a typo in comments by @lewis-yeung in #27047
• Save TB logs as part of push_to_hub by @muellerzr in #27022
• Added huggingface emoji instead of the markdown format by @shettyvarshaa in #27091
• [T5Tokenizer] Fix fast and extra tokens by @ArthurZucker in #27085
• Revert "add exllamav2 arg" by @ArthurZucker in #27102
• Add early stopping for Bark generation via logits processor by @isaac-chung in #26675
• Provide alternative when warning on use_auth_token by @Wauplin in #27105
• Fix no split modules underlying modules by @SunMarc in #27090
• [core/ gradient_checkpointing] Refactor GC - part 2 by @younesbelkada in #27073
• fix detr device map by @SunMarc in #27089
• Added Telugu [te] translation for README.md in main by @hakunamatata1997 in #27077
• translate transformers_agents.md to Chinese by @jiaqiw09 in #27046
• Fix docstring and type hint for resize by @daniilgaltsev in #27104
• [Typo fix] flag config in WANDB by @SoyGema in #27130
• Fix slack report failing for doctest by @ydshieh in #27042
• [FA2/ Mistral] Revert previous behavior with right padding + forward by @younesbelkada in #27125
• Fix data2vec-audio note about attention mask by @gau-nernst in #27116
• remove the obsolete code related to fairscale FSDP by @statelesshz in #26651
• Fix some tests using "common_voice" by @ydshieh in #27147
• [tests / Quantization] Fix bnb test by @younesbelkada in #27145
• make tests of pytorch_example device agnostic by @statelesshz in #27081
• Remove some Kosmos-2 copied from by @ydshieh in #27149
• 🌐 [i18n-ZH] Translate serialization.md into Chinese by @yyLeaves in #27076
• Translating en/main_classes folder docs to Japanese 🇯🇵 by @rajveer43 in #26894
• Device agnostic trainer testing by @statelesshz in #27131
• Fix: typos in README.md by @THEFZNKHAN in #27154
• [KOSMOS-2] Update docs by @NielsRogge in #27157
• deprecate function get_default_device in tools/base.py by @statelesshz in #26774
• Remove broken links to s-JoL/Open-Llama by @CSRessel in #27164
• [docstring] Fix docstring for AltCLIPTextConfig, AltCLIPVisionConfig and AltCLIPConfig by @AksharGoyal in #27128
• [doctring] Fix docstring for BlipTextConfig, BlipVisionConfig by @Hangsiin in #27173
• Disable CI runner check by @ydshieh in #27170
• fix: Fix typical_p behaviour broken in recent change by @njhill in #27165
• Trigger CI if tiny_model_summary.json is modified by @ydshieh in #27175
• Shorten the conversation tests for speed + fixing position overflows by @Rocketknight1 in #26960
• device agnostic pipelines testing by @statelesshz in #27129
• Backward compatibility fix for the Conversation class by @Rocketknight1 in #27176
• [Quantization / tests ] Fix bnb MPT test by @younesbelkada in #27178
• Fix dropout in StarCoder by @susnato in #27182
• translate traning.md to chinese by @jiaqiw09 in #27122
• [docs] Update CPU/GPU inference docs by @stevhliu in #26881
• device agnostic models testing by @statelesshz in #27146
• Unify warning styles for better readability by @oneonlee in #27184
• 🌐 [i18n-ZH] Translate tflite.md into Chinese by @yyLeaves in #27134
• device agnostic fsdp testing by @statelesshz in #27120
• Fix docstring get maskformer resize output image size by @wesleylp in #27196
• Fix the typos and grammar mistakes in CONTRIBUTING.md. by @THEFZNKHAN in #27193
• Fixing docstring in get_resize_output_image_size function by @wesleylp in #27191
• added unsqueeze_dim to apply_rotary_pos_emb by @ShashankMosaicML in #27117
• Added cache_block_outputs option to enable GPTQ for non-regular models by @AlexKoff88 in #27032
• Add TensorFlow implementation of ConvNeXTv2 by @neggles in #25558
• Fix docstring in get_oneformer_resize_output_image_size func by @wesleylp in #27207
• improving TimmBackbone to support FrozenBatchNorm2d by @rafaelpadilla in #27160
• Translate task summary to chinese by @jiaqiw09 in #27180
• Fix CPU offload + disk offload tests by @LysandreJik in #27204
• Enable split_batches through TrainingArguments by @muellerzr in #26798
• support bf16 by @etemadiamd in #25879
• Reproducible checkpoint for npu by @statelesshz in #27208
• [core / Quantization] Fix for 8bit serialization tests by @younesbelkada in #27234

Significant community contributions

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

• @jungnerd
  • 🌐 [i18n-KO] Translated semantic_segmentation.md to Korean (#26515)
• @statelesshz
  • Extend Trainer to enable Ascend NPU to use the fused Adamw optimizer when training (#26194)
  • remove SharedDDP as it is deprecated (#25702)
  • remove the obsolete code related to fairscale FSDP (#26651)
  • make tests of pytorch_example device agnostic (#27081)
  • Device agnostic trainer testing (#27131)
  • deprecate function get_default_device in tools/base.py (#26774)
  • device agnostic pipelines testing (#27129)
  • device agnostic models testing (#27146)
  • device agnostic fsdp testing (#27120)
  • Reproducible checkpoint for npu (#27208)
• @sgugger
  • Docstring check (#26052)
• @yyLeaves
  • add zh translation for installation (#26084)
  • [i18n-ZH] Translated fast_tokenizers.md to Chinese (#26910)
  • 🌐 [i18n-ZH] Translate multilingual into Chinese (#26935)
  • 🌐 [i18n-ZH] Translate create_a_model.md into Chinese (#27026)
  • 🌐 [i18n-ZH] Translate custom_models.md into Chinese (#27065)
  • 🌐 [i18n-ZH] Translate serialization.md into Chinese (#27076)
  • 🌐 [i18n-ZH] Translate tflite.md into Chinese (#27134)
• @sinking-point
  • In assisted decoding, pass model_kwargs to model's forward call (fix prepare_input_for_generation in all models) (#25242)
• @rajveer43
  • add japanese documentation (#26138)
  • Translating en/internal folder docs to Japanese 🇯🇵 (#26747)
  • Refactor code part in documentation translated to japanese (#26900)
  • Translating en/main_classes folder docs to Japanese 🇯🇵 (#26894)
• @alvarorichard
  • translation brazilian portuguese (#26769)
• @hakunamatata1997
  • Added Telugu [te] translations (#26828)
  • Added Telugu [te] translation for README.md in main (#27077)
• @jiaqiw09
  • Translate pipeline_tutorial.md to chinese (#26954)
  • translate preprocessing.md to Chinese (#26955)
  • translate transformers_agents.md to Chinese (#27046)
  • translate traning.md to chinese (#27122)
  • Translate task summary to chinese (#27180)
• @neggles
  • Add TensorFlow implementation of ConvNeXTv2 (#25558)