* fix warnings in deberta
* fix copies
* Revert "fix copies"
This reverts commit 324cb3fed1.
* fix copies
* fix copies again
* revert changes to whitespace that make style did since it results in an infinite chain of fix-copies
* argh
Co-authored-by: Sander Land <sander@chatdesk.com>
* added type hints for Yolos Pytorch model
* make fixup
* Update src/transformers/models/yolos/convert_yolos_to_pytorch.py
* Update src/transformers/models/yolos/convert_yolos_to_pytorch.py
* Update src/transformers/models/yolos/convert_yolos_to_pytorch.py
Co-authored-by: Matt <rocketknight1@gmail.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* Partial TF port for ESM model
* Add ESM-TF tests
* Add the various imports for TF-ESM
* TF weight conversion almost ready
* Stop ignoring the decoder weights in PT
* Add tests and lots of fixes
* fix-copies
* Fix imports, add model docs
* Add get_vocab() to tokenizer
* Fix vocab links for pretrained files
* Allow multiple inputs with a sep
* Use EOS as SEP token because ESM vocab lacks SEP
* Correctly return special tokens mask from ESM tokenizer
* make fixup
* Stop testing unsupported embedding resizing
* Handle TF bias correctly
* Skip all models with slow tokenizers in the token classification test
* Fixing the batch/unbatcher of pipelines to accomodate the `None` being
passed around.
* Fixing pipeline bug caused by slow tokenizer being different.
* Update src/transformers/models/esm/modeling_tf_esm.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Update src/transformers/models/esm/modeling_tf_esm.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Update src/transformers/models/esm/modeling_tf_esm.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Update set_input_embeddings and the copyright notices
Co-authored-by: Your Name <you@example.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* add type hints to mctct
* run auto style corrections
* change torch.bool to bool#
* Update src/transformers/models/mctct/modeling_mctct.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* Remove optional tags for attention_mask and head_mask'
* fix optional tags'
* Update src/transformers/models/mctct/modeling_mctct.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* Remove key word argument X from pipeline predict and transform methods
As __call__ of pipeline clasees require one positional argument, passing
the input as a keyword argument inside predict, transform methods, causing
__call__ to fail. Hence in this commit the keyword argument is modified
into positional argument.
* Implement basic tests for scikitcompat pipeline interface
* Seperate tests instead of running with parameterized based on framework as both frameworks will not be active at the same time
* update feature extractor params
* update attention mask handling
* fix doc and pipeline test
* add warning when skipping test
* add whisper translation and transcription test
* fix build doc test
* Correct whisper processor
* make fix copies
* remove sample docstring as it does not fit whisper model
* Update src/transformers/models/whisper/modeling_whisper.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* fix, doctests are passing
* Nit
* last nit
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Improve error messaging for ASR pipeline.
- Raise error early (in `_sanitize`) so users don't waste time trying to
run queries with invalid params.
- Fix the error was after using `config.inputs_to_logits_ratio` so our
check was masked by the failing property does not exist.
- Added some manual check on s2t for the error message.
No non ctc model seems to be used by the default runner (they are all
skipped).
* Removing pdb.
* Stop the early error it doesn't really work :(.
* GPTTOkenizer dependency removed from deberta class
Fixup
made the Deberta Tokenizer fast independent of GPT-2 tokenizer
Copied annotation added
Done the dependency removal
* Added some missing copied statement
* Added some copied statements
* add suport for non fast tf bert tokenizer
* add tests for non fast tf bert tokenizer
* fix fast bert tf tokenizer flag
* double tokenizers list on tf tokenizers test to aovid breaking zip on test output equivalence
* reformat code with black to comply with code quality checks
* trigger ci
* fix BLOOM ONNX config
- `value` params have `seq_len` as their 2nd axe as opposed to other models which have it as 3rd
Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>
* [Doctest] Add `configuration_bigbird_pegasus.py` and `configuration_big_bird`
[Doctest] Re-style `configuration_big_bird.py`
* [Doctest] One python instruction per line
* [Doctest] Fix styling
* [Doctest] More styling fixes
* Added type hints for TF: XLNet
* Added type hints for TF: XLNet
* Added type hints for TF: XLNet
* Added type hints for TF: XLNet
* Added type hints for TF: XLNet
* Added type hints for TF: XLNet
* Add type hints for XLnet (TF)
* Added type hints for XLnet (TF)
* Update src/transformers/models/xlnet/modeling_tf_xlnet.py
