GitLab

fix typo:

from:

 "model = TFAutoModelForQuestionAnswering("distilbert-base-uncased")"

to:
model = TFAutoModelForQuestionAnswering.from_pretrained("distilbert-base-uncased")

Update backbones.md

Add missing space in warning

* First draft

* More improvements

* More improvements

* More improvements

* More improvements

* Add docs

* Remove file

* Add copied from

* Address comments

* Address comments

* Address comments

* Fix style

* Update docs

* Convert all checkpoints, add integration test

* Rename checkpoints

* Add pretrained backbone attributes

* Fix default config

* Address comment

* Add figure to docs

* Fix bug thanks to @xenova

* Update conversion script

* Fix integration test

* fix hfoptions

* revert changes to other files

* fix

* update doc

* revert

* typo fix

* refine

* add dtypes

* Update docs/source/en/perf_train_cpu.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/perf_train_cpu.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/perf_train_cpu.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* no comma

* use avx512-vnni

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Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Changed type hinting for all attention inputs to 'Optional[Tuple[torch.FloatTensor,...]] = None'

* Fixed the ruff formatting issue

* fixed type hinting for all hidden_states to 'Optional[Tuple[torch.FloatTensor, ...]] = None'

* Changed type hinting in these 12 scripts modeling_dpr.py,modeling_nat.py,idefics/vision.py,modeling_tf_dpr.py,modeling_luke.py,modeling_swin.py,modeling_tf_swin.py,modeling_blip.py,modeling_tf_blip.py,modeling_donut_swin.py,modeling_dinat.py,modeling_swinv2.py

* test fail update

* fixed type hinting for these 15 scripts modeling_xlnet.py,modeling_tf_xlnet.py,modeling_led.py,modeling_tf_led.py,modleing_rwkv.py,modeling_dpt.py,modeling_tf_cvt.py,modeling_clip.py,modeling_flax_clip.py,modeling_tf_clip.py,modeling_longformer.py,modeling_tf_longformer.py,modeling_siglip.py,modeling_clap.py,modeling_git.py

* Changed type hinting in these 12 scripts modeling_dpr.py,modeling_nat.py,idefics/vision.py,modeling_tf_dpr.py,modeling_luke.py,modeling_swin.py,modeling_tf_swin.py,modeling_blip.py,modeling_tf_blip.py,modeling_donut_swin.py,modeling_dinat.py,modeling_swinv2.py

* test fail update

* Removed the myvenv file

* Fixed type hinting for these 8 scripts modeling_tvlt.py,modeling_sam.py,modeling_tf_sam.py,modeling_tvp.py,modeling_rag.py,modeling_tf_rag.py,modeling_tf_xlm.py,modeling_xlm.py

* config

* optim

* pre deploy

* deploy

* save weights, memory, troubleshoot, non-Trainer

* done

* Use save_safetensor to disable safe serialization for XLA

https://github.com/huggingface/transformers/issues/28438

* Style fixup

* fix the function load_balancing_loss_func in Mixtral_Moe to include attention_mask

* format code using black and ruff

* skip computing mask if attention_mask=None

* add tests for load balancing loss Mixtral-Moe

* fix assert loss is different in mixtral_test

* fix pad_leng

* use assertNotAlmostEqual and print to debug

* remove print for debug

* minor updates

* reduce rtol and atol

Fixing grammatical errors in the text

fix a hidden bug of `GenerationConfig`, now the `generation_config.json` can be loaded successfully (#28604)

* fix a hidden bug of GenerationConfig

* keep `sort_keys=True` to maintain visibility

* Update src/transformers/generation/configuration_utils.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update configuration_utils.py

in case `obj` is a list, check the items in the list

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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Remove deprecated eager_serving fn

* Fix the input_signature docstring while I'm here

convert token id to list in .decode()

* add dataloader prefetch factor in training args and trainer

* remove trailing spaces

* prevent dataloader_num_workers == 0 and dataloader_prefetch_factor != None

dataloader_prefetch_factor works only when data is loaded in a different process as the main one. This commit adds the necessary checks to avoid having prefetch_factor set when there is no such process.

* Remove whitespaces in empty line

* Update src/transformers/training_args.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/training_args.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/training_args.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/training_args.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

Fix windows err

Fix copy/paste error msg typo

* Enable instantiating model with pretrained backbone weights

* Update tests so backbone checkpoint isn't passed in

* Remove doc updates until changes made in modeling code

* Clarify pretrained import

* Update configs - docs and validation check

* Update src/transformers/utils/backbone_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Clarify exception message

* Update config init in tests

* Add test for when use_timm_backbone=True

* Small test updates

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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

Enable safetensors conversion from PyTorch to other frameworks without the torch requirement (#27599)

* Initial commit

* Requirements & tests

* Tests

* Tests

* Rogue import

* Rogue torch import

* Cleanup

* Apply suggestions from code review
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* bfloat16 management

* Sanchit's comments

* Import shield

* apply suggestions from code review

* correct bf16

* rebase

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Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: sanchit-gandhi <sanchit@huggingface.co>

get default device through `PartialState().default_device` as it has been officially released (#27256)

get default device through `PartialState().default_device` as it has
been officially released

Co-authored-by: Pashmina Cameron <11311835+pashminacameron@users.noreply.github.com>

Only import class if sp available

* Update image_processing_deformable_detr.py

* Changes after running make fix-copies

Update modeling_gpt_neox.py

* Update convert_llava_weights_to_hf.py script

* Remove config update of adding padding to `vocab_size` and `text_config.vocab_size` which causes `ValueError` exception.
* Remove keys that ends with `inv_freq` from the state dict.
* Add examples and instructions for creating `model_state_dict.bin` that can be used by the script.

* Update convert_llava_weights_to_hf.py

* Update convert_vipllava_weights_to_hf.py

* Fix lr_scheduler

* Fix lr scheduler

Add tip to custom model docs

* avoid root logger's level being changed

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

Fix missing bbox in LayoutLM signature

* fix dtype issue

* add a test

* update copied from mentions

* nits

* fixup

* fix copies

* Apply suggestions from code review

* [DETA] fix freeze/unfreeze function

* Update src/transformers/models/deta/modeling_deta.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/deta/modeling_deta.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* add freeze/unfreeze test case in DETA

* fix type

* fix typo 2

* fix : enable aux and enc loss in training pipeline

* Add unsynced variables from original DETA for training

* modification for passing CI test

* make style

* make fix

* manual make fix

* change deta_modeling_test of configuration 'two_stage' default to TRUE and minor change of dist checking

* remove print

* divide configuration in DetaModel and DetaForObjectDetection

* image smaller size than 224 will give topk error

* pred_boxes and logits should be equivalent to two_stage_num_proposals

* add missing part in DetaConfig

* Update src/transformers/models/deta/modeling_deta.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* add docstring in configure and prettify TO DO part

* change distribute related code to accelerate

* Update src/transformers/models/deta/configuration_deta.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update tests/models/deta/test_modeling_deta.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* protect importing accelerate

* change variable name to specific value

* wrong import

* fix aux_loss in conditional_detr

* add test aux_loss

* add aux_loss test in deta and table_transformer

* fix yolos since it doesn't have auxiliary function

* fix maskformer auxiliary_loss related code

* make style

* change param 'auxiliary_loss' to 'use_auxiliary_loss'

* change param 'auxiliary_loss' to 'use_auxiliary_loss' in tests

* make style & fix-copies, also revert yolos related parameter

* revert variable name 'use_auxiliary_loss' to 'auxiliary_loss' due to DetrConfig

* revert variable name in yolos

* revert maskformer

* add aux_loss test in maskformer

* make style

* Update src/transformers/models/yolos/configuration_yolos.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Allow non-special tokens to be added

* Add test, fix token adding code

* Revert changes to id_to_token and token_to_id

* Update the ESM tokenizer to be a bit more standardized

* Update src/transformers/models/esm/tokenization_esm.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update convert_llava_weights_to_hf.py

Fix call to `tokenizer.add_tokens`

* Add special_tokens to tokenizer.add_tokens in convert_vipllava_weights_to_hf.py

First draft

* remove elif xpu

* remove redudant code