* 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>
* 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`.
* 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>
* 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* Fix dependency issue with outdated requirement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 ff11df1c81.
* 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>
* Test workflow
* Build doc
* Make a clean build
* Add doc config
* Restore other workflows
* Final job
* Print something in else statements
* Pull before making changes
* Fix doc examples: name '...' is not defined
* remove >>> and ... in some docstrings in visual_bert
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
