IDEFICS
The IDEFICS model was proposed in [OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents](https://huggingface.co/papers/2306.16527) by Hugo Laurençon, Lucile Saulnier, Léo Tronchon, Stas Bekman, Amanpreet Singh, Anton Lozhkov, Thomas Wang, Siddharth Karamcheti, Alexander M. Rush, Douwe Kiela, Matthieu Cord, Victor Sanh
IDEFICS is the first open state-of-the-art visual language model at the 80B scale!
The model accepts arbitrary sequences of image and text and produces text, similarly to a multimodal ChatGPT.
Blogpost: [hf.co/blog/idefics](http://huggingface.co/blog/idefics)
Playground: [HuggingFaceM4/idefics_playground](http://huggingface.co/spaces/HuggingFaceM4/idefics_playground)
* new model: IDEFICS via HuggingFaceM4 by stas00 in 24796
MPT
MPT has been added and is now officially supported within Transformers. The repositories from MosaicML have been updated to work best with the model integration within Transformers.
* [`MPT`] Add MosaicML's `MPT` model to transformers by ArthurZucker & younesbelkada in 24629
GPTQ Integration
GPTQ quantization is now supported in Transformers, through the `optimum` library. The backend relies on the [auto_gptq](https://github.com/PanQiWei/AutoGPTQ) library, from which we use the `GPTQ` and `QuantLinear` classes.
See below for an example of the API, quantizing a model using the new `GPTQConfig` configuration utility.
py
from transformers import AutoModelForCausalLM, AutoTokenizer, GPTQConfig
model_name = "facebook/opt-125m"
tokenizer = AutoTokenizer.from_pretrained(model_name)
config = GPTQConfig(bits=4, dataset = "c4", tokenizer=tokenizer, group_size=128, desc_act=False)
works also with device_map (cpu offload works but not disk offload)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, quantization_config=config)
Most models under [TheBloke](https://huggingface.co/TheBloke) namespace with the suffix `GPTQ` should be supported, for example, to load a GPTQ quantized model on `TheBloke/Llama-2-13B-chat-GPTQ` simply run (after installing latest optimum and auto-gptq libraries):
python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "TheBloke/Llama-2-13B-chat-GPTQ"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
For more information about this feature, we recommend taking a look at the following announcement blogpost: https://huggingface.co/blog/gptq-integration
* GPTQ integration by SunMarc in 25062
Pipelines
A new pipeline, dedicated to text-to-audio and text-to-speech models, has been added to Transformers. It currently supports the 3 text-to-audio models integrated into `transformers`: `SpeechT5ForTextToSpeech`, `MusicGen` and `Bark`.
See below for an example:
py
from transformers import pipeline
classifier = pipeline(model="suno/bark")
output = pipeline("Hey it's HuggingFace on the phone!")
audio = output["audio"]
sampling_rate = output["sampling_rate"]
* Add Text-To-Speech pipeline by ylacombe in 24952
Classifier-Free Guidance decoding
Classifier-Free Guidance decoding is a text generation technique developed by EleutherAI, announced in [this paper](https://arxiv.org/abs/2306.17806). With this technique, you can increase prompt adherence in generation. You can also set it up with negative prompts, ensuring your generation doesn't go in specific directions. See its [docs](https://huggingface.co/docs/transformers/internal/generation_utils#transformers.UnbatchedClassifierFreeGuidanceLogitsProcessor) for usage instructions.
* add CFG for .generate() by Vermeille in 24654
Task guides
A new task guide going into Visual Question Answering has been added to Transformers.
* VQA task guide by MKhalusova in 25244
Model deprecation
We continue the deprecation of models that was introduced in https://github.com/huggingface/transformers/pull/24787.
By deprecating, we indicate that we will stop maintaining such models, but there is no intention of actually removing those models and breaking support for them (they might one day move into a separate repo/on the Hub, but we would still add the necessary imports to make sure backward compatibility stays). The main point is that we stop testing those models. The usage of the models drives this choice and aims to ease the burden on our CI so that it may be used to focus on more critical aspects of the library.
* Deprecate unused OpenLlama architecture by tomaarsen in 24922
Translation Efforts
There are ongoing efforts to translate the transformers' documentation in other languages. These efforts are driven by groups independent to Hugging Face, and their work is greatly appreciated further to lower the barrier of entry to ML and Transformers.
If you'd like to kickstart such an effort or help out on an existing one, please feel free to reach out by opening an issue.
* 🌐 [i18n-KO] Translated`tasks/document_question_answering.md` to Korean by jungnerd in 24588
* 🌐 [i18n-KO] Fixed Korean and English `quicktour.md` by wonhyeongseo in 24664
* 🌐 [i18n-KO] Updated Korean `serialization.md` by wonhyeongseo in 24686
* 🌐 [i18n-KO] Translated performance.md to Korean by augustinLib in 24883
* 🌐 [i18n-KO] Translated `testing.md` to Korean by Sunmin0520 in 24900
* 🌐 [i18n-KO] Translated `perf_train_cpu.md` to Korean by seank021 in 24911
* 🌐 [i18n-KO] Translated `<tf_xla>.md` to Korean by 54data in 24904
* 🌐 [i18n-KO] Translated `perf_hardware.md` to Korean by augustinLib in 24966
* 🌐 [i18n-KO] Translated `hpo_train.md` to Korean by harheem in 24968
* 🌐 [i18n-KO] Translated `perf_infer_cpu.md` to Korean by junejae in 24920
* 🌐 [i18n-KO] Translated pipeline_webserver.md to Korean by kihoon71 in 24828
* 🌐 [i18n-KO] Translated `transformers_agents.md` to Korean by sim-so in 24881
* 🌐 [i18n-KO] Translated `perf_infer_gpu_many.md` to Korean by heuristicwave in 24943
* 🌐 [i18n-KO] Translated `perf_infer_gpu_one.md` to Korean by eenzeenee in 24978
* 🌐 [i18n-KO] Translated `add_tensorflow_model.md` to Korean by keonju2 in 25017
* 🌐 [i18n-KO] Translated `perf_train_cpu_many.md` to Korean by nuatmochoi in 24923
* 🌐 [i18n-KO] Translated `add_new_model.md` to Korean by mjk0618 in 24957
* 🌐 [i18n-KO] Translated `model_summary.md` to Korean by 0525hhgus in 24625
* 🌐 [i18n-KO] Translated `philosophy.md` to Korean by TaeYupNoh in 25010
* 🌐 [i18n-KO] Translated `perf_train_tpu_tf.md` to Korean by 0525hhgus in 25433
* 🌐 [i18n-KO] Translated docs: ko: pr_checks.md to Korean by sronger in 24987
Explicit input data format for image processing
Addition of `input_data_format` argument to image transforms and ImageProcessor methods, allowing the user to explicitly set the data format of the images being processed. This enables processing of images with non-standard number of channels e.g. 4 or removes error which occur when the data format was inferred but the channel dimension was ambiguous.
python
import numpy as np
from transformers import ViTImageProcessor
img = np.random.randint(0, 256, (4, 6, 3))
image_processor = ViTImageProcessor()
inputs = image_processor(img, image_mean=0, image_std=1, input_data_format="channels_first")
* Input data format by amyeroberts in 25464
* Add input_data_format argument, image transforms by amyeroberts in 25462
Documentation clarification about efficient inference through `torch.scaled_dot_product_attention` & Flash Attention
Users are not aware that it is possible to force dispatch `torch.scaled_dot_product_attention` method from `torch` to use Flash Attention kernels. This leads to considerable speedup and memory saving, and is also compatible with quantized models. We decided to make this explicit to users in the documentation.
* [Docs / BetterTransformer ] Added more details about flash attention + SDPA : https://github.com/huggingface/transformers/pull/25265
In a nutshell, one can just run:
diff
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("facebook/opt-350m")
model = AutoModelForCausalLM.from_pretrained("facebook/opt-350m").to("cuda")
convert the model to BetterTransformer
model.to_bettertransformer()
input_text = "Hello my dog is cute and"
inputs = tokenizer(input_text, return_tensors="pt").to("cuda")
+ with torch.backends.cuda.sdp_kernel(enable_flash=True, enable_math=False, enable_mem_efficient=False):
outputs = model.generate(**inputs)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
to enable Flash-attenion in their model. However, this feature does not support padding yet.
FSDP and DeepSpeed Changes
Users will no longer encounter CPU RAM OOM when using FSDP to train very large models in multi-gpu or multi-node multi-gpu setting.
Users no longer have to pass `fsdp_transformer_layer_cls_to_wrap` as the code now use `_no_split_modules` by default which is available for most of the popular models. DeepSpeed Z3 init now works properly with Accelerate Launcher + Trainer.
* add util for ram efficient loading of model when using fsdp by pacman100 in 25107
* fix fsdp checkpointing issues by pacman100 in 24926
* fsdp fixes and enhancements by pacman100 in 24980
* fix deepspeed load best model at end when the model gets sharded by pacman100 in 25057
* resolving zero3 init when using accelerate config with Trainer by pacman100 in 25227
* fix z3 init when using accelerate launcher by pacman100 in 25589
Breaking changes
Default optimizer in the `Trainer` class
The default optimizer in the `Trainer` class has been updated to be `adam_torch` rather than our own `adam_hf`, as the official Torch optimizer is more robust and fixes some issues.
In order to keep the old behavior, ensure that you pass "adamw_hf" as the `optim` value in your `TrainingArguments`.
* 🚨🚨🚨Change default from `adamw_hf` to `adamw_torch` 🚨🚨🚨 by muellerzr in 25109
ViVit and EfficientNet rescale bugfix
There was an issue with the definition of the rescale of values with ViVit and EfficientNet. These have been fixed, but will result in different model outputs for both of these models. To understand the change and see what needs to be done to obtain previous results, please take a look at the following PR.
* 🚨🚨🚨 Fix rescale ViVit Efficientnet by amyeroberts in 25174
* 🚨🚨🚨 Vivit update default rescale_factor value by amyeroberts in 25547
Removing softmax for the image classification EfficientNet class
The `EfficientNetForImageClassification` model class did not follow conventions and added a softmax to the model logits. This was removed so that it respects the convention set by other models.
In order to obtain previous results, pass the model logits through a softmax.
* 🚨🚨🚨 Remove softmax for EfficientNetForImageClassification 🚨🚨🚨 by amyeroberts in 25501
Bug fixes with SPM models
Some SPM models had issues with their management of added tokens. Namely the `Llama` and `T5`, among others, were behaving incorrectly. These have been updated in https://github.com/huggingface/transformers/pull/25224.
An option to obtain the previous behavior was added through the `legacy` flag, as explained in the PR linked above.
* 🚨🚨🚨 [`SPM`] Finish fix spm models 🚨🚨🚨 by ArthurZucker in 25224
Bugfixes and improvements
* Disable ipex env var if false by muellerzr in 24885
* Check for accelerate env var when doing CPU only by muellerzr in 24890
* Avoid some pipeline tasks to use `use_cache=True` by ydshieh in 24893
* Update tested versions in READMEs by EliahKagan in 24895
* Fix `test_model_parallelism` for `FalconModel` by ydshieh in 24914
* Fixed issue where ACCELERATE_USE_CPU="False" results in bool(True) by madhavajay in 24907
* fix typo in BARK_PRETRAINED_MODEL_ARCHIVE_LIST by 21jun in 24902
* Fix minor llama2.md model doc typos by tmc in 24909
* [`Llama2`] replace `self.pretraining_tp` with `self.config.pretraining_tp` by younesbelkada in 24906
* [doc] `image_processing_vilt.py` wrong default documented by stas00 in 24931
* Add multi-label text classification support to pytorch example by ranchlai in 24770
* replace no_cuda with use_cpu in test_pytorch_examples by statelesshz in 24944
* Generate: sequence bias can handle same terminations by gante in 24822
* Update processing_vision_text_dual_encoder.py by premsa in 24950
* Fix `main_input_name` in `src/transformers/keras_callbacks.py` by ydshieh in 24916
* [DOCS] Example for `LogitsProcessor` class by shauray8 in 24848
* fix type annotations for arguments in training_args by shauray8 in 24550
* [`RWKV`] Add Gradient Checkpointing support for RWKV by younesbelkada in 24955
* Change logic for logging in the examples by muellerzr in 24956
* Contrastive Search peak memory reduction by blbadger in 24120
* Fallback for missing attribute `Parameter.ds_numel` by apoorvkh in 24942
* fix fsdp checkpointing issues by pacman100 in 24926
* fix: cast input pixels to appropriate dtype for image_to_text pipelines by JimAllanson in 24947
* fsdp fixes and enhancements by pacman100 in 24980
* Fix missing spaces in system prompt of Llama2 tokenizer by chenjoya in 24930
* [`LlamaConfig`] Nit: pad token should be None by default by ArthurZucker in 24958
* Remove tokenizers from the doc table by sgugger in 24963
* Avoid importing all models when instantiating a pipeline by sgugger in 24960
* Fix type annotation for deepspeed training arg by sgugger in 24988
* Use main_input_name for include_inputs_for_metrics by sgugger in 24993
* Fix `llama` tokenization doctest by ydshieh in 24990
* [`bnb`] Add simple check for bnb import by younesbelkada in 24995
* [`Llama`] remove persistent `inv_freq` tensor by ArthurZucker in 24998
* improve from_pretrained for zero3 multi gpus mode by 1ytic in 24964
* Move template doc file to md by sgugger in 25004
* [check_config_docstrings.py] improve diagnostics by stas00 in 25012
* [`logging.py`] set default `stderr` path if `None` by ArthurZucker in 25033
* fix(integrations): store serialized `TrainingArgs` to `wandb.config` without sanitization. by parambharat in 25035
* [docs] Performance docs tidy up, part 1 by MKhalusova in 23963
* Support GatedRepoError + use raise from by Wauplin in 25034
* Better handling missing SYS in llama conversation tokenizer by ichernev in 24997
* Add dispatch_batches to training arguments by muellerzr in 25038
* Fix typo in LlamaTokenizerFast docstring example by sbrunk in 25018
* Make more test models smaller by sgugger in 25005
* Pvt model by Xrenya in 24720
* compute_loss in trainer failing to label shift for PEFT model when label smoothing enabled. by njbrake in 25044
* [`8bit`] Fix 8bit corner case with Blip2 8bit by younesbelkada in 25047
* Better error message when signal is not supported on OS by sgugger in 25049
* [`RWKV`] Add note in doc on `RwkvStoppingCriteria` by ArthurZucker in 25055
* Generate - add beam indices output in contrained beam search by gante in 25042
* [Docs] fix rope_scaling doc string by kashif in 25072
* Fix last models for common tests that are too big. by sgugger in 25058
* fix: add TOC anchor link by eenzeenee in 25066
* Set `TF32` flag for PyTorch cuDNN backend by XuehaiPan in 25075
* Fix broken link in README_hd.md by susnato in 25067
* replace `per_gpu_eval_batch_size` with `per_device_eval_batch_size` in readme of multiple-choice task by statelesshz in 25078
* [`generate`] Only warn users if the `generation_config`'s `max_length` is set to the default value by ArthurZucker in 25030
* Fix: repeat per sample for SAM image embeddings by xk-huang in 25074
* [DOCS] add example NoBadWordsLogitsProcessor by SoyGema in 25046
* Allow generic composite models to pass more kwargs by ydshieh in 24927
* [ `ForSequenceClassification`] Support `left` padding by ArthurZucker in 24979
* [`TF`] Also apply patch to support left padding by ArthurZucker in 25085
* Edit err message and comment in `test_model_is_small` by connor-henderson in 25087
* [ `PreTrainedTokenizerFast`] Keep properties from fast tokenizer by ArthurZucker in 25053
* Hotfix for failing `MusicgenForConditionalGeneration` tests by ydshieh in 25091
* [`T5`, `MT5`, `UMT5`] Add [T5, MT5, UMT5]ForSequenceClassification by sjrl in 24726
* Fix doctest by ydshieh in 25031
* fix tied_params for meta tensor by SunMarc in 25101
* documentation for llama2 models by shauray8 in 25102
* Fix `PvtModelIntegrationTest::test_inference_fp16` by ydshieh in 25106
* Add descriptive docstring to TemperatureLogitsWarper by nablabits in 24892
* fix "UserWarning: Creating a tensor from a list of numpy.ndarrays is … by liucw2012 in 24772
* update `use_auth_token` -> `token` by ydshieh in 25083
* Fix past CI after 24334 by ydshieh in 25113
* Move common image processing methods to BaseImageProcessor by amyeroberts in 25089
* Fix ViT docstring regarding default dropout values. by ebezzam in 25118
* MaskFormer - enable return_dict in order to compile by amyeroberts in 25052
* Move center_crop to BaseImageProcessor by amyeroberts in 25122
* fix deepspeed load best model at end when the model gets sharded by pacman100 in 25057
* fix delete all checkpoints when save_total_limit is set to 1 by Pbihao in 25136
* [`T5/LlamaTokenizer`] default legacy to `None` to not always warn by ArthurZucker in 25131
* Clarify 4/8 bit loading log message by BramVanroy in 25134
* [`MptConfig`] support from pretrained args by ArthurZucker in 25116
* Add offload support to Bark by ylacombe in 25037
* More `token` things by ydshieh in 25146
* Add bloom flax by sanchit-gandhi in 25094
* Add new model in doc table of content by sgugger in 25148
* Fix `.push_to_hub` and cleanup `get_full_repo_name` usage by Wauplin in 25120
* Add test when downloading from gated repo by Wauplin in 25039
* override .cuda() to check if model is already quantized by ranchlai in 25166
* Represent query_length in a different way to solve jit issue by jiqing-feng in 25164
* make run_generation more generic for other devices by statelesshz in 25133
* added compiled model support for inference by markovalexander in 25124
* Update `use_auth_token` -> `token` in example scripts by ydshieh in 25167
* [`Mpt`] Fix mpt slow test by younesbelkada in 25170
* [`InstructBlip`] Fix instructblip slow test by younesbelkada in 25171
* Fix beam search to sample at least 1 non eos token by yonigottesman in 25103)
* [MusicGen] Fix integration tests by sanchit-gandhi in 25169
* Musicgen: CFG is manually added by gante in 25173
* Better error message in `_prepare_output_docstrings` by ydshieh in 25202
* [`PreTrainedModel`] Wrap `cuda` and `to` method correctly by younesbelkada in 25206
* Fix `all_model_classes` in `FlaxBloomGenerationTest` by ydshieh in 25211
* [quantization.md] fix by stas00 in 25190
* [`pipeline`] revisit device check for pipeline by younesbelkada in 25207
* Update tiny model info. and pipeline testing by ydshieh in 25213
* Fix docker image build failure by ydshieh in 25214
* make build_mpt_alibi_tensor a method of MptModel so that deepspeed co… by sywangyi in 25193
* [`Pix2Struct`] Fix pix2struct cross attention by younesbelkada in 25200
* [`Docs`/`quantization`] Clearer explanation on how things works under the hood. + remove outdated info by younesbelkada in 25216
* [`MPT`] Add `require_bitsandbytes` on MPT integration tests by younesbelkada in 25201
* [`Detr`] Fix detr BatchNorm replacement issue by younesbelkada in 25230
* Move rescale dtype recasting to match torchvision ToTensor by amyeroberts in 25229
* Fix set of model parallel in the Trainer when no GPUs are available by sgugger in 25239
* fix get_keys_to_not_convert() to return correct modules for full precision inference by ranchlai in 25105
* add pathname and line number to logging formatter in debug mode by ranchlai in 25203
* Add `token` arugment in example scripts by ydshieh in 25172
* resolving zero3 init when using accelerate config with Trainer by pacman100 in 25227
* Update rescale tests - cast to float after rescaling to reflect 25229 by amyeroberts in 25259
* Fix some bugs for two stage training of deformable detr by jypjypjypjyp in 25045
* [DOCS] Add example and modified docs of EtaLogitsWarper by ashishthomaschempolil in 25125
* Fix return_dict_in_generate bug in InstructBlip generate function by eohomegrownapps in 25246
* Remove `pytest_options={"rA": None}` in CI by ydshieh in 25263
* recommend DeepSpeed's Argument Parsing documentation by BurnzZ in 25268
* [MMS] Fix mms by patrickvonplaten in 25267
* CI with `num_hidden_layers=2` 🚀🚀🚀 by ydshieh in 25266
* CI with `pytest_num_workers=8` for torch/tf jobs by ydshieh in 25274
* Docs: Update list of `report_to` logging integrations in docstring by tomaarsen in 25281
* Update InstructBLIP & Align values after rescale update by amyeroberts in 25209
* Docs: separate generate section by gante in 25235
* Update bark doc by ylacombe in 25234
* add generate method to SpeechT5ForTextToSpeech by ylacombe in 25233
* Add timeout parameter to load_image function by rolisz in 25184
* [JAX] Bump min version by sanchit-gandhi in 25286
* [small] llama2.md typo by H-Huang in 25295
* Fix typo: Roberta -> RoBERTa by MrGeislinger in 25302
* Move usage of deprecated logging.warn to logging.warning by PeterJCLaw in 25310
* Give more memory in test_disk_offload by sgugger in 25315
* Generate: get generation mode as an enum by gante in 25292
* Add offline mode for agents by sgugger in 25226
* Deal with nested configs better in base class by sgugger in 25237
* Document check copies by sgugger in 25291
* Make `bark` could have tiny model by ydshieh in 25290
* Document toc check and doctest check scripts by sgugger in 25319
* [Whisper] Better error message for outdated generation config by sanchit-gandhi in 25298
* Remove jnp.DeviceArray since it is deprecated. by mariecwhite in 24875
* Update TF pin in docker image by ydshieh in 25343
* Generalize CFG to allow for positive prompts by oobabooga in 25339
* Loosen output shape restrictions on GPT-style models by calpt in 25188
* Allow `trust_remote_code` in example scripts by Jackmin801 in 25248
* Generate: remove Marian hack by gante in 25294
* Fix more offload edge cases by ydshieh in 25342
* Migrate Trainer from `Repository` to `upload_folder` by sgugger in 25095
* Adding more information in help parser on train_file and validation_file by pphuc25 in 25324
* [DOCS] Add `NoRepeatNGramLogitsProcessor` Example for `LogitsProcessor` class by Rishab26 in 25186
* Docs: Added benchmarks for `torch.compile()` for vision models by merveenoyan in 24748
* Add mask2former fp16 support by pedrohml in 25093
* [DOCS] Add descriptive docstring to MinNewTokensLength by nablabits in 25196
* Register ModelOutput subclasses as supported torch.utils._pytree nodes by ringohoffman in 25358
* Fix `test_model_parallelism` by ydshieh in 25359
* Add warning for missing attention mask when pad tokens are detected by hackyon in 25345
* [ASR Pipeline] Clarify return timestamps by sanchit-gandhi in 25344
* MaskFormer, Mask2Former - replace einsum for tracing by amyeroberts in 25297
* Load state in else by muellerzr in 25318
* Fix `token` in example template by ydshieh in 25351
* Enable tests to run on third-party devcies by statelesshz in 25327
* Fix `torch_job` worker(s) crashing by ydshieh in 25374
* Generate: add config-level validation by gante in 25381
* Fix missing usage of `token` by ydshieh in 25382
* Use small config for `OneFormerModelTest.test_model_with_labels` by ydshieh in 25383
* Add copied from for image processor methods by amyeroberts in 25121
* change version by SunMarc in 25387
* [DOCS] Add example for `TopPLogitsWarper` by chiral-carbon in 25361
* 16059 - Add missing type hints for ASTModel by nablabits in 25364
* rm useless condition since the previous condition contains it. by jiqing-feng in 25403
* Fix path for dynamic module creation by sgugger in 25402
* YOLOS - Revert default return_pixel_mask value by amyeroberts in 25404
* Docs: introduction to generation with LLMs by gante in 25240
* Generate: length validation by gante in 25384
* Improve training args by statelesshz in 25401
* Generate: generation config validation fixes in docs by gante in 25405
* 16059 - Add extra type hints for AltCLIPModel by nablabits in 25399
* Generate: lower severity of parameterization checks by gante in 25407
* Update Bark generation configs and tests by ylacombe in 25409
* aligned sample_beam output selection with beam_search by hukuda222 in 25375
* Enable passing number of channels when inferring data format by amyeroberts in 25412
* Bark: flexible generation config overload by gante in 25414
* [DINOv2] Update pooler output by NielsRogge in 25392
* Doc checks by sgugger in 25408
* Generation: strict generation config validation at save time by gante in 25411
* [WavLM] Fix Arxiv link and authors by sanchit-gandhi in 25415
* Generate: Load generation config when `device_map` is passed by gante in 25413
* Fix rendering for `torch.compile()` docs by merveenoyan in 25432
* Add `examples` to tests to run when `setup.py` is modified by ydshieh in 25437
* Fix issue with ratio evaluation steps and auto find batch size by muellerzr in 25436
* docs: add LLaMA-Efficient-Tuning to awesome-transformers by statelesshz in 25441
* Fix for 25437 by ydshieh in 25454
* Refactor image processor testers by amyeroberts in 25450
* Switch Transformers: remove overwritten beam sample test by gante in 25458
* Reuse the cache created for latest `main` on PRs/branches if `setup.py` is not modified by ydshieh in 25445
* Update run_translation.py broken link example Pytoch by SoyGema in 25461
* Add input_data_format argument, image transforms by amyeroberts in 25462
* Mark flaky tests by amyeroberts in 25463
* Revert "Reuse the cache created for latest `main` on PRs/branches" by ydshieh in 25466
* import required torch and numpy libraries by eze1376 in 25483
* fix : escape key of start_token from special characters before search end_token in token2json function of DonutProcessor by nour-elkamel in 25472
* Remove logging code in TF Longformer that fails to compile by Rocketknight1 in 25496
* Add type hints to Blip2QFormer, BigBirdForQA and ConditionalDetr family models by nablabits in 25488
* Set can_generate for SpeechT5ForTextToSpeech by ylacombe in 25493
* MaskFormer post_process_instance_segmentation bug fix convert out side of loop by amyeroberts in 25497
* fix gptq nits by SunMarc in 25500
* Conditional DETR type hint fix by Rocketknight1 in 25505
* Check for case where `auxiliary_head` is `None` in `UperNetPreTrainedModel` by mmurray in 25514
* add __repr__ to the BitsAndBytesConfig class by ranchlai in 25517
* Make training args fully immutable by muellerzr in 25435
* Use dynamic past key-values shape in TF-Whisper by Rocketknight1 in 25523
* [TYPO] fix typo/format in quicktour.md by lishukan in 25519
* Fix nested configs of Jukebox by sgugger in 25533
* Marian: post-hack-fix correction by gante in 25459
* Document the test fetcher by sgugger in 25521
* Generate: fix default max length warning by gante in 25539
* fix vit hybrid test by SunMarc in 25543
* Fix `MaskFormerModelIntegrationTest` OOM by ydshieh in 25544
* More frozen args by muellerzr in 25540
* Input data format by amyeroberts in 25464
* [ASR Pipeline] Fix init with timestamps by sanchit-gandhi in 25438
* More utils doc by sgugger in 25457
* Update trainer.py by yundai424 in 25553
* Add documentation to dynamic module utils by sgugger in 25534
* Fix MPT CI by ydshieh in 25548
* Fix `torch.fx` tests on nightly CI by ydshieh in 25549
* YOLOS - reset default return_pixel_mask value by amyeroberts in 25559
* Skip `test_onnx_runtime_optimize` for now by ydshieh in 25560
* [`Docs`] Fix un-rendered images by younesbelkada in 25561
* Adds `TRANSFORMERS_TEST_DEVICE` by vvvm23 in 25506
* Skip `test_beam_search_xla_generate_simple` for `T5` by ydshieh in 25566
* [`resize_embedding`] Introduce `pad_to_multiple_of` and guidance by ArthurZucker in 25088
* [`SwitchTransformers`] Remove unused module by ArthurZucker in 25427
* Inconsistency in PreTrainedModel.resize_token_embeddings When ZeRO3 Is Enabled by sinamoeini in 25394
* [`NllbMoe`] Update code to properly support loss computation by ArthurZucker in 25429
* [`Tests`] Fix failing 8bit test by younesbelkada in 25564
* Revert "change version by SunMarc in 25387)"
* add util for ram efficient loading of model when using fsdp by pacman100 in 25107
* Skip `test_contrastive_generate` for `TFXLNet` by ydshieh in 25574
* add warning for 8bit optimizers by SunMarc in 25575
* Fix typo in example code by amelietamreymond in 25583
* Suggestions on Pipeline_webserver by kihoon71 in 25570
* [`Docs` / `BetterTransformer` ] Added more details about flash attention + SDPA by younesbelkada in 25265
* Added missing parenthesis in call to is_fsdp_enabled by marma in 25585
* Replaces calls to `.cuda` with `.to(torch_device)` in tests by vvvm23 in 25571
* [`split_special_tokens`] Add support for `split_special_tokens` argument to encode by ArthurZucker in 25081
* [`Llama`] remove prompt and fix prefix finetuning by ArthurZucker in 25565
* [Time series Informer] fix dtype of cumsum by kashif in 25431
* fix z3 init when using accelerate launcher by pacman100 in 25589
* [`TokenizerFast`] Fix setting prefix space in __init__ by ArthurZucker in 25563
* Make TTS automodels importable by osanseviero in 25595
* reattach hooks when using `resize_token_embeddings` by SunMarc in 25596
* Ignore all exceptions from signal in dynamic code by sgugger in 25623
* Fix PEFT integration failures on nightly CI by younesbelkada in 25624
* Run doctest for new files by ydshieh in 25588
* Fix test_modeling_mpt typo in model id by JuanFKurucz in 25606
Significant community contributions
The following contributors have made significant changes to the library over the last release:
* ranchlai
* Add multi-label text classification support to pytorch example (24770)
* override .cuda() to check if model is already quantized (25166)
* fix get_keys_to_not_convert() to return correct modules for full precision inference (25105)
* add pathname and line number to logging formatter in debug mode (25203)
* add __repr__ to the BitsAndBytesConfig class (25517)
* wonhyeongseo
* 🌐 [i18n-KO] Fixed Korean and English `quicktour.md` (24664)
* 🌐 [i18n-KO] Updated Korean `serialization.md` (24686)
* Sunmin0520
* 🌐 [i18n-KO] Translated `testing.md` to Korean (24900)
* Xrenya
* Pvt model (24720)
* susnato
* Fix broken link in README_hd.md (25067)
* Add Pop2Piano (21785)
* sjrl
* [`T5`, `MT5`, `UMT5`] Add [T5, MT5, UMT5]ForSequenceClassification (24726)
* Jackmin801
* Allow `trust_remote_code` in example scripts (25248)
* mjk0618
* 🌐 [i18n-KO] Translated `add_new_model.md` to Korean (24957)