* Kill model archive maps
* Fixup
* Also kill model_archive_map for MaskedBertPreTrainedModel
* Unhook config_archive_map
* Tokenizers: align with model id changes
* make style && make quality
* Fix CI
* pass on tokenizer to pipeline
* order input names when convert to onnx
* update style
* remove unused imports
* make ordered inputs list needs to be mutable
* add test custom bert model
* remove unused imports
* better api
* improve automatic setting of global attention mask
* fix longformer bug
* fix global attention mask in test
* fix global attn mask flatten
* fix slow tests
* update docstring
* update docs and make more robust
* improve attention mask
* add multiple choice for longformer
* add models to docs
* adapt docstring
* add test to longformer
* add longformer for mc in init and modeling auto
* fix tests
* make transformers-cli cross-platform
Using "scripts" is a useful option in setup.py particularly when you want to get access to non-python scripts. However, in this case we want to have an entry point into some of our own Python scripts. To do this in a concise, cross-platfom way, we can use entry_points.console_scripts. This change is necessary to provide the CLI on different platforms, which "scripts" does not ensure. Usage remains the same, but the "transformers-cli" script has to be moved (be part of the library) and renamed (underscore + extension)
* make style & quality
* added LongformerForQuestionAnswering
* add LongformerForQuestionAnswering
* fix import for LongformerForMaskedLM
* add LongformerForQuestionAnswering
* hardcoded sep_token_id
* compute attention_mask if not provided
* combine global_attention_mask with attention_mask when provided
* update example in docstring
* add assert error messages, better attention combine
* add test for longformerForQuestionAnswering
* typo
* cast gloabl_attention_mask to long
* make style
* Update src/transformers/configuration_longformer.py
* Update src/transformers/configuration_longformer.py
* fix the code quality
* Merge branch 'longformer-for-question-answering' of https://github.com/patil-suraj/transformers into longformer-for-question-answering
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Add Type Hints to modeling_utils.py Closes#3911
Add Type Hints to methods in `modeling_utils.py`
Note: The coverage isn't 100%. Mostly skipped internal methods.
* Reformat according to `black` and `isort`
* Use typing.Iterable instead of Sequence
* Parameterize Iterable by its generic type
* Use typing.Optional when None is the default value
* Adhere to style guideline
* Update src/transformers/modeling_utils.py
* Update src/transformers/modeling_utils.py
Co-authored-by: Julien Chaumond <chaumond@gmail.com>
* Warn the user about max_len being on the path to be deprecated.
* Ensure better backward compatibility when max_len is provided to a tokenizer.
* Make sure to override the parameter and not the actual instance value.
* Format & quality
* Adds predict stage for glue tasks, and generate result files which could be submitted to gluebenchmark.com website.
* Use Split enum + always output the label name
Co-authored-by: Julien Chaumond <chaumond@gmail.com>
