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* expand install instructions

* fix

* white space

* rewrite as discussed in the PR

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* change the wording to encourage issue report
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Remove redundant test_head_masking = True flags

* Remove all redundant test_head_masking flags in PyTorch test_modeling_* files

* Make test_head_masking = True as a default choice in test_modeling_tf_commong.py

* Remove all redundant test_head_masking flags in TensorFlow
test_modeling_tf_* files

* Put back test_head_masking=False fot TFT5 models

* Fix computation of attention_probs when head_mask is provided.
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>

* Apply changes to the template
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* Allow partial loading of a cached tokenizer

* Warning > Info

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

* Raise error if not local_files_only
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* tests: add integration tests for new Bort model

* bort: add conversion script from Gluonnlp to Transformers 🚀



* bort: minor cleanup (BORT -> Bort)

* add docs

* make fix-copies

* clean doc a bit

* correct docs

* Update docs/source/model_doc/bort.rst
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update docs/source/model_doc/bort.rst
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* correct dialogpt doc

* correct link

* Update docs/source/model_doc/bort.rst

* Update docs/source/model_doc/dialogpt.rst
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* make style
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* fix --lr_scheduler_type choices

* rewrite to fix for all enum-based cl args

* cleanup

* adjust test

* style

* Proposal that should work

* Remove needless code

* Fix test
Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>

* Allow --arg Value for booleans in HfArgumentParser

* Update last test

* Better error message

* Whenresuming training from checkpoint, Trainer loads model

* Finish cleaning tests

* Address review comment

* Use global_step from state

* add tpu_zone and gcp_project in training_args_tf.py

* make style

Co-authored-by: kykim <kykim>

* Add a flag for find_unused_parameters

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

* Remove negation
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Start cleaning BERT

* Clean BERT and all those depends of it

* Fix attribute name

* Apply style

* Apply Sylvain's comments

* Apply Lysandre's comments

* remove unused import

Co-authored-by: Tomohide Shibata <tomshiba@yahoo-corp.jp>

* Rework documentation

* Update the template

* Trigger CI

* Restore the warning but with the TF logger

* Update convbert doc

pipeline.

- If table is empty then the line that contain `answer[0]` will fail.
- This PR add a check to prevent `answer[0]`.
- Also adds an early check for presence of `table` and `query` to
prevent late failure and give better error message.
- Adds a few tests to make sure these errors are correctly raised.

* Fix auto-resume training from checkpoint

* style fixes

* update jaxlib

* Update setup.py

* update table

* finalize convbert

* finalize convbert

* fix

* fix

* fix

* push

* fix

* tf image patches

* fix torch model

* tf tests

* conversion

* everything aligned

* remove print

* tf tests

* fix tf

* make tf tests pass

* everything works

* fix init

* fix

* special treatment for sepconv1d

* style

* 🙏🏽



* add doc and cleanup

* add electra test again

* fix doc

* fix doc again

* fix doc again

* Update src/transformers/modeling_tf_pytorch_utils.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/models/conv_bert/configuration_conv_bert.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update docs/source/model_doc/conv_bert.rst
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

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

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

* conv_bert -> convbert

* more fixes from review

* add conversion script

* dont use pretrained embed

* unused config

* suggestions from julien

* some more fixes

* p -> param

* fix copyright

* fix doc

* Update src/transformers/models/convbert/configuration_convbert.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* comments from reviews

* fix-copies

* fix style

* revert shape_list
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Commit the last step on world_process_zero in WandbCallback

* Use the environment variable WANDB_LOG_MODEL as a default value in WandbCallback

* get cross attns

* add cross-attns doc strings

* fix typo

* line length

* Apply suggestions from code review
Co-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>
Co-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>

* Add a debug print

* Adapt Trainer to use smdistributed if available

* Forgotten parenthesis

* Real check for sagemaker

* Donforget to define device...

* Woopsie, local)rank is defined differently

* Update since local_rank has the proper value

* Remove debug statement

* More robust check for smdistributed

* Quality

* Deal with key not present error

* Pad to 8x for fp16 multiple choice example (#9752)

* Pad to 8x for fp16 squad trainer example (#9752)

* Pad to 8x for fp16 ner example (#9752)

* Pad to 8x for fp16 swag example (#9752)

* Pad to 8x for fp16 qa beam search example (#9752)

* Pad to 8x for fp16 qa example (#9752)

* Pad to 8x for fp16 seq2seq example (#9752)

* Pad to 8x for fp16 glue example (#9752)

* Pad to 8x for fp16 new ner example (#9752)

* update script template #9752

* Update examples/multiple-choice/run_swag.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update examples/question-answering/run_qa.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update examples/question-answering/run_qa_beam_search.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* improve code quality #9752
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* We most likely don't want special tokens in this output.

* Adding `skip_special_tokens=True` to FillMaskPipeline

- It's backward incompatible.
- It makes for sense for pipelines to remove references to
special_tokens (all of the other pipelines do that).
- Keeping special tokens makes it hard for users to actually remove them
  because all models have different tokens (<s>, <cls>, [CLS], ....)

* Fixing `token_str` in the same vein, and actually fix the tests too !

* Add head_mask/decoder_head_mask for TF BART models

* Add head_mask and decoder_head_mask input arguments for TF BART-based
models as a TF counterpart to the PR #9569

* Add test_headmasking functionality to tests/test_modeling_tf_common.py

* TODO: Add a test to verify that we can get a gradient back for
importance score computation

* Remove redundant #TODO note

Remove redundant #TODO note from tests/test_modeling_tf_common.py

* Fix assertions

* Make style

* Fix ...Model input args and adjust one new test

* Add back head_mask and decoder_head_mask to BART-based ...Model
after the last commit

* Remove head_mask ande decoder_head_mask from input_dict
in TF test_train_pipeline_custom_model as these two have different
shape than other input args (Necessary for passing this test)

* Revert adding global_rng in test_modeling_tf_common.py