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* Add type hints for LukeModel

* Add type hints for entitypairclassification

* Remove blank space
Co-authored-by: bhavika <bhavika@debian-BULLSEYE-live-builder-AMD64>

* Can choose framework for ONNX export

* Fix docstring

* Add type hints for TFDistilBert

* Update src/transformers/models/distilbert/modeling_tf_distilbert.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* First pass

* Fixup

* Fix broken tests

* Make unpack_inputs the first decorator

* Replace input_processing

* move unpack_inputs

* Fix checkpoint name in docstring example
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Spanish translation of the file training.mdx

* Settings - Spanish translation of the file training.mdx

* Latest changes to the Spanish translation of the training.mdx file

* Delete Hugging.mdx

* Last changes to the training fil Espanish version

* Latest modifications

* Latest changes, document ready for PR

* Nits
Co-authored-by: Yhary Arias <yharystefa@gmail.com>
Co-authored-by: Omar U. Espejel <espejelomar@gmail.com>

Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

* Change unpacking of TF mobilebert inputs to use decorator

* Move unpack_inputs as the top decorator

* make fixup
Co-authored-by: ChienVM <chien_vm@detomo.co.jp>

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

* Make TF pt-tf equivalence test more aggressive

* Fix for TFConvNextModelTest and TFTransfoXLModelTest

* fix kwargs for outputs

* clean-up

* Add docstring for check_outputs()

* remove: need to rename encoder-decoder

* clean-up

* send PyTorch things to the correct device

* Add back the accidentally removed test case in test_pt_tf_model_equivalence()

* Fix: change to tuple before calling check_outputs()

* Fix: tfo could be a list

* use to_tuple()

* allow tfo only to be tuple or tensor

* allow tfo to be list or tuple for now + style change

* minor fix

* remove np.copy and update comments

* tfo -> tf_output, same for pt

* Add more detailed comment

* remove the incorrect comment
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

Configuration `tied-embeddings-all` implies `tied-embeddings-src`

Fix Loading of Flax(Speech)EncoderDecoderModel kwargs from PreTrained Encoder-Decoder Checkpoints (#16056)

* Fix Loading of Flax(Speech)EncoderDecoderModel kwargs from PreTrained Encoder-Decoder Checkpoints

* change wording

* Make Camembert great again!

* Add Camembert to TensorFlow ONNX tests

* Add missing type hints for all flavors of LayoutLMv2 PyTorch models.

* Fixed return types and added type hints for LayoutLM.

* Fix removed arguments which breaks tests.

* [WIP] add support for bf16 mode

* prep for bf16

* prep for bf16

* fix; zero2/bf16 is ok

* check bf16 is available

* test fixes

* enable zero3_bf16

* config files

* docs

* split stage_dtype; merge back to non-dtype-specific config file

* fix doc

* cleanup

* cleanup

* bfloat16 => bf16 to match the PR changes

* s/zero_gather_fp16_weights_on_model_save/zero_gather_16bit_weights_on_model_save/; s/save_fp16_model/save_16bit_model/

* test fixes/skipping

* move

* fix

* Update docs/source/main_classes/deepspeed.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* backticks

* cleanup

* cleanup

* cleanup

* new version

* add note about grad accum in bf16
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* gather z3 params for new_lm_head

* Update src/transformers/modeling_utils.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* 📝 first draft of audio/vision guides

* ✨ make fixup

* 🖍 fix typo

* 🖍 close parentheses

* 🖍 apply feedback

* 🖍 apply feedback, make fixup

* 🖍 more fixup for perceiver

* 🖍 apply feedback

* ✨ make fixup

* 🖍 fix data collator

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

* Add missing type hints for all flavors of RoBERTa PyTorch models.

* Fixed type hints for all classes and fixed return types.

* Rebuild deepspeed

* Apply suggestions from code review
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* 📝 first draft

* 🖍 apply feedback

* 🖍 apply feedback

* add possibility to softly regulate length when using sampling method in model.generate() function

* fix test config, fix formatting

* fix rag integration, fix docstyling

* fix wrong docstring

* change param to tuple, add test

* fix old param in rag_model, remove unused import

* change test according to new param

* fix formatting

* fix test case

* fix doc style

* move start_length calculation to Logitprocessor

* add possibility to softly regulate length when using sampling method in model.generate() function

* fix rag integration, fix docstyling

* fix test config, fix formatting

* change param to tuple, add test

* fix old param in rag_model, remove unused import

* add possibility to softly regulate length when using sampling method in model.generate() function

* change param to tuple, add test

* fix old param in rag_model, remove unused import

* remove unused import

* fix small errors

* fix test

* add possibility to softly regulate length when using sampling method in model.generate() function

* fix test config, fix formatting

* fix rag integration, fix docstyling

* change param to tuple, add test

* fix old param in rag_model, remove unused import

* change test according to new param

* fix test case

* move start_length calculation to Logitprocessor

* add possibility to softly regulate length when using sampling method in model.generate() function

* fix rag integration, fix docstyling

* fix test config, fix formatting

* change param to tuple, add test

* fix old param in rag_model, remove unused import

* add possibility to softly regulate length when using sampling method in model.generate() function

* fix test config, fix formatting

* fix rag integration, fix docstyling

* add possibility to softly regulate length when using sampling method in model.generate() function

* fix rag integration, fix docstyling

* change param to tuple, add test

* fix old param in rag_model, remove unused import

* fix small errors

* Update src/transformers/generation_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/generation_utils.py

* Update src/transformers/generation_utils.py

* fix docstring, add type ind model rag

* fix docstrings

* introduce seq_length variable for cleaner code

* fix black formatting

* add input_ids_seq_length to modeling_rag

* add input_ids_seq_length to test

* retrigger checks

* retrigger checks
Co-authored-by: Kevin Bondzio <kev@AIM-LAP-02.local>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Kevin Bondzio <kev@AIM-LAP-02.fritz.box>

* Adding type annotations for TFRoBERTa

* Add type hints to TFRobertaModel too

* Add type annotations for BERT and copies

* make fixup