GitLab

* 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>

* Fixed trainer total_flos relaoding in distributed mode

* logging flos at the end of training

* improve flax

* refactor

* typos

* Update src/transformers/modeling_flax_utils.py

* Apply suggestions from code review

* Update src/transformers/modeling_flax_utils.py

* fix typo

* improve error tolerance

* typo

* correct nasty saving bug

* fix from pretrained

* correct tree map

* add note

* correct weight tying

* Fix Trainer with remove_unused_columns=False

* Typo

fix typo
Co-authored-by: johnson <johnson@github.com>

* finish

* fix copy

* fix wav2vec2 tok

* up

* MOD: fit chinese wwm to new datasets

* MOD: move wwm to new folder

* MOD: formate code

* Styling

* MOD add param and recover trainer

* MOD: add token_type_ids method for big bird

* MOD: format code

* MOD: format code
Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>

* explain/link to good first issue

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

And update README to explain the work-in-progress!

* remove boiler plate code

* adapt roberta

* correct docs

* finish refactor

First of the new and more idiomatic TF examples!

* bring doc up to date

* fix

* Pass metric_key_prefix as kwarg to on_evaluate

* Replace eval_loss with metric_key_prefix_loss

* Default to "eval" if metric_key_prefix not in kwargs

* Add kwargs to CallbackHandler.on_evaluate signature

* Revert "Add kwargs to CallbackHandler.on_evaluate signature"

This reverts commit 8d4c85ed512f558f7579d36771e907b3379947b7.

* Revert "Pass metric_key_prefix as kwarg to on_evaluate"

This reverts commit 7766bfe2718601230ae593d37b1317bd53cfc075.

* Extract metric_key_prefix from metrics

* 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>

This PR fixes a bug that most likely somehow got exposed (not caused) by https://github.com/huggingface/transformers/pull/11318 - surprisingly the same test worked just fine before that other PR.

* Honor contributors to models

* Fix typo

* Address review comments

* Add more authors

* Removed `max_length` from being mandatory within `generate`.

- Moving on to fully using `StoppingCriteria` for `greedy` and `sample`
modes.
- `max_length` still used for `beam_search` and `group_beam_search`
(Follow up PR)
- Fixes a bug with MaxLengthStoppingCriteria (we should stop as soon a
we hit the max_length, the comparison needs to be or equal, that affects
the tests).
- Added options to use `logits_processor` and `stopping_criteria`
directly within `generate` function (so some users can define their own
`logits_processor` and `stopping_criteria`).
- Modified the backward compat tests to make sure we issue a warning.

* Fix `max_length` argument in `generate`.

* Moving validate to being functional.

- Renamed `smax_length` to `stoppping_max_length`.

* Removing `logits_processor` and `stopping_criteria` from `generate`
arguments.

* Deepcopy.

* Fix global variable name.

Add an error message that fires when Reformer is not in training mode, but one runs .backward() (#11117)

* Update to use datasets remove_cloumns method

* Quality

* create local attention mask ones

* remove old method, address patricks comment

* remove update function

* update

* refactor more

* refactor

* initial changes

* modified evaluation

* updated evaluation

* updated evaluation on text translation example script

* added translation example script

* Formatted translation example script

* Reformatted translation example

* Fixed evaluation bug and added support for other tokenisers

* Fixed evaluation bug and added support for other tokenisers

* Added translation example script

* Formatted summarization example script

* Removed typos from summarization example script

* fix the placement on device with fp16_full_eval

* deepspeed never goes on device

* Update language_modeling.py

in "class TextDatasetForNextSentencePrediction(Dataset)", double considering "self.tokenizer.num_special_tokens_to_add(pair=True)" 

so, i remove self.block_size, and add parameter for "def create_examples_from_document". like "class LineByLineWithSOPTextDataset" do

* Update language_modeling.py