GitLab

* [WIP] Model card defaults

* finetuned_from default value

* Add all mappings to the mapping file

* Be more defensive on finetuned_from arg

* Add default task tag

* Separate tags from tasks

* Edge case for dataset

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Don't log anything before logging is setup in examples

* Last example

* Add text_column_name and label_column_name to run_ner args

* Minor fix: grouping for text and label column name

* Add option to long only once in multinode training

* Use an alternate property

* add headers to main doc

* Apply suggestions from code review

* update

* upload

* Autogenerate model cards from the Trainer

* ModelCard deprecated

* Fix test

* Style

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Address review comments

* Quality

* With all metadata

* Metadata

* Post-merge conflict mess

* Data args and all examples

* Default license and languages when possible
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Split checkpoint from model_name_or_path in examples

* Address review comments

* Address review comments

* added changes for uniformity

* modified files

* corrected typo

* fixed qa scripts

* fix typos

* fixed predict typo in qa no trainer

* fixed test file

* reverted trainer changes

* reverted trainer changes in custom exmaples

* updated readme

* added changes in deepspeed test

* added changes for predict and eval

* Initial support for upload to hub

* push -> upload

* Fixes + examples

* Fix torchhub test

* Torchhub test I hate you

* push_model_to_hub -> push_to_hub

* Apply mixin to other pretrained models

* Remove ABC inheritance

* Add tests

* Typo

* Run tests

* Install git-lfs

* Change approach

* Add push_to_hub to all

* Staging test suite

* Typo

* Maybe like this?

* More deps

* Cache

* Adapt name

* Quality

* MOAR tests

* Put it in testing_utils

* Docs + torchhub last hope

* Styling

* Wrong method

* Typos

* Update src/transformers/file_utils.py
Co-authored-by: Julien Chaumond <julien@huggingface.co>

* Address review comments

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Julien Chaumond <julien@huggingface.co>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Base move

* Examples reorganization

* Update references

* Put back test data

* Move conftest

* More fixes

* Move test data to test fixtures

* Update path

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Address review comments and clean
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* First third

* Styling and fix mistake

* Quality

* All the rest

* Treat %s and %d

* typo

* Missing )

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Add minimum version check in examples

* Style

* No need for new line maybe?

* Add helpful comment

* reverted changes of logging and saving metrics

* added max_sample arguments

* fixed code

* white space diff

* reformetting code

* reformatted code

* updated logging and saving metrics

* space removal

* make executable

* make executable

* same for the template

* cleanup

* 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>

* Auto-resume training from checkpoint

* Update examples/text-classification/run_glue.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Roll out to other examples
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Switch metrics in run_ner to datasets

* Add flag to return all metrics

* Upstream (and rename) sortish_sampler

* Revert "Upstream (and rename) sortish_sampler"

This reverts commit e07d0dcf650c2bae36da011dd76c77a8bb4feb0d.

* Allow example to use a revision and work with private models

* Copy to other examples and template

* Styling

* Use word_ids to get labels in run_ner

* Add sanity check

* Fix run_ner script

* Pin datasets

* <small>tiny typo</small>

* Tokenizers: ability to load from model subfolder

* use subfolder for local files as well

* Uniformize model shortcut name => model id

* from s3 => from huggingface.co
Co-authored-by: Quentin Lhoest <lhoest.q@gmail.com>

The new run_ner.py script tries to run prediction on the input
test set `datasets["test"]`, but it should be the tokenized set
`tokenized_datasets["test"]`

* Add new token classification example

* Remove txt file

* Add test

* With actual testing done

* Less warmup is better

* Update examples/token-classification/run_ner_new.py
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

* Address review comments

* Fix test

* Make Lysandre happy

* Last touches and rename

* Rename in tests

* Address review comments

* More run_ner -> run_ner_old
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

* Add more token classification examples

* POS tagging example

* Phrase chunking example

* PR review fixes

* Add conllu to third party list (used in token classification examples)