GitLab

* Fix docs

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

* Code quality
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* Fix code examples

* Fix code example

* Initial commit for Keras model cards

* Revert accidental change

* make style

* make style

* make style

* Fix PR comments

* Move repo creation to __init__

* Fixes to README.md creation

* Partial progress for proper card creation on `push_to_hub`

* Proper card creation from `push_to_hub` plus fixes for malformed model cards

* Fixes for model card creation outside the callback

* Adding a model card creation test

* Putting the model card creation test in the right file.
Good job, Matt.

* make style

* Fix model card test temp dir usage

* Fix model card creation when no optimizer present

* Fixes for when training history not present

* Fix accidental edit to test_modeling_common

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

* Fake new model

* Fix doc-building test job

* Is this the problem?

* Another try

* Typo

* Clean up

* Can we do without -e ?

* Clean setup

* Fix broken links to distillation on index page of documentation

* Fix broken link for distillation in main README

* Run make fixup

* Adding support for multiple mask tokens.

- Original implem: https://github.com/huggingface/transformers/pull/10222

Co-authored-by: njafer <naveen.jafer@oracle.com>

* In order to accomodate optionally multimodal models like Perceiver

we add information to the tasks to specify tasks where we know for sure
if we need the tokenizer/feature_extractor or not.

* Adding info in the documentation about multi masks.

+ marked as experimental.

* Add a copy() to prevent overriding the same tensor over and over.

* Fixup.

* Adding small test for multi mask with real values..
Co-authored-by: njafer <naveen.jafer@oracle.com>

* use jax and jnp instead of numpy in data_loader

* return batches as np.ndarray

* Adding some slow test to check for perceiver at least from a high level.

* Re-enabling fast tests for Perceiver ImageClassification.

* Perceiver might try to run without Tokenizer (Fast doesn't exist) and
with FeatureExtractor some text only pipelines.

* Oops.

* Adding a comment for `update_config_with_model_class`.

* Remove `model_architecture` to get `tiny_config`.

* Finalize rebase.

* Smarter way to handle undefined FastTokenizer.

* Remove old code.

* Addressing some nits.

* Don't instantiate `None`.

* Convert Trainer doc page to MarkDown

* Fix repo consistency

* Fix the doc build test job

* First draft

* Improve docstring + clean up tests

* Remove unused code

* Add check in case one doesn't provide a preprocessor

* avoid tf.tile in embeddings

* remove more tf.tile in embeddings

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

* Mention no images added to repository

* Update CONTRIBUTING.md
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Wip on metadata update

* Most of the script

* Add a job to auto-update the transformers metadata

* Style

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

* Fix doc examples: cannot import name

* remove copy because of some necessary minor changes (maybe add copy to the individual methods instead)

* Keep copy with some modifications
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

- Do not run image-classification pipeline (_CHECKPOINT_FOR_DOC uses the checkpoint for
langage, which cannot load a FeatureExtractor so current logic fails).
- Add a safeguard to not run tests when `tokenizer_class` or
`feature_extractor_class` **are** defined, but cannot be loaded
This happens for Perceiver for the "FastTokenizer" (which doesn't exist
so None) and FeatureExtractor (which does exist but cannot be loaded
because the checkpoint doesn't define one which is reasonable for the
said checkpoint)
- Added `get_vocab` function to `PerceiverTokenizer` since it is used by
`fill-mask` pipeline when the argument `targets` is used to narrow a
subset of possible values.
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* Migrate docs to mdx

* Update TAPAS docs

* Remove lines

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

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

* Add pt/tf switch to code examples

* More improvements

* Improve docstrings

* More improvements
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

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

* Add some nicety flags for better controlling evaluation.

* Fix dependency issue with outdated requirement

* Add additional flag to example to ensure eval is done

* Wrap code into main function for accelerate launcher to find

* Fix valid batch size flag in readme

* Add note to install git-lfs when initializing/training the model

* Update examples/research_projects/codeparrot/scripts/arguments.py
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>

* Update examples/research_projects/codeparrot/README.md
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>

* Revert "Wrap code into main function for accelerate launcher to find"

This reverts commit ff11df1c810d4df198d04b827538eb4572147ba3.

* Fix formatting issue

* Move git-lfs instructions to installation section

* Add a quick check before code generation for code evaluation

* Fix styling issue

* Update examples/research_projects/codeparrot/scripts/human_eval.py
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>

* Make iterable dataset use passed in tokenizer rather than globally defined one
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
Co-authored-by: ncoop57 <nac33@students.uwf.edu>

* correct changes

* add comment

* use custom training arguments

* update tests

* document MoE model approach

* additional info from Samyam

* fix

* Fixing tests for perceiver (texts)

* For MaskedLM