* Result of black 23.1
* Update target to Python 3.7
* Switch flake8 to ruff
* Configure isort
* Configure isort
* Apply isort with line limit
* Put the right black version
* adapt black in check copies
* Fix copies
* initial commit
* First draft that gets outputs without crashing!
* Add all the ported openfold dependencies
* testing
* Restructure config files for ESMFold
* Debugging to find output discrepancies
* Mainly style
* Make model runnable without extra deps
* Remove utils and merge them to the modeling file
* Use correct gelu and remove some debug prints
* More cleanup
* Update esm docs
* Update conversion script to support ESMFold properly
* Port some top-level changes from ESMFold repo
* Expand EsmFold docstrings
* Make attention_mask optional (default to all 1s)
* Add inference test for ESMFold
* Use config and not n kwargs
* Add modeling output class
* Remove einops
* Remove chunking in ESM FFN
* Update tests for ESMFold
* Quality
* REpo consistency
* Remove tree dependency from ESMFold
* make fixup
* Add an error in case my structure map function breaks later
* Remove needless code
* Stop auto-casting the LM to float16 so CPU tests pass
* Stop auto-casting the LM to float16 so CPU tests pass
* Final test updates
* Split test file
* Copyright and quality
* Unpin PyTorch to see built doc
* Fix config file to_dict() method
* Add some docstrings to the output
* Skip TF checkpoint tests for ESM until we reupload those
* make fixup
* More docstrings
* Unpin to get even with main
* Flag example to write
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.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>
