* <small>tiny typo</small>
* Tokenizers: ability to load from model subfolder
* use subfolder for local files as well
* Uniformize model shortcut name => model id
* from s3 => from huggingface.co
Co-authored-by: Quentin Lhoest <lhoest.q@gmail.com>
* Put models in subfolders
* Styling
* Fix imports in tests
* More fixes in test imports
* Sneaky hidden imports
* Fix imports in doc files
* More sneaky imports
* Finish fixing tests
* Fix examples
* Fix path for copies
* More fixes for examples
* Fix dummy files
* More fixes for example
* More model import fixes
* Is this why you're unhappy GitHub?
* Fix imports in conver command
* Use the CI to identify failing tests
* Remove from all examples and tests
* More default switch
* Fixes
* More test fixes
* More fixes
* Last fixes hopefully
* Use the CI to identify failing tests
* Remove from all examples and tests
* More default switch
* Fixes
* More test fixes
* More fixes
* Last fixes hopefully
* Run on the real suite
* Fix slow tests
* Fix passing token_type_ids during GPT2DoubleHeadsModel.generate() if used
and for GPT2LMHeadModel too
* Update tests to check token_type_ids usage in GPT2 models
* Simply insert T5Tokenizer's prepare_seq2seq_batch
* Update/Add some 'import'
* fix RunTimeError caused by '.view'
* Moves .view related error avoidance from seq2seq_trainer to inside prophetnet
* Update test_tokenization_prophetnet.py
* Format the test code with black
* Re-format the test code
* Update test_tokenization_prophetnet.py
* Add importing require_torch in the test code
* Add importing BatchEncoding in the test code
* Re-format the test code on Colab
* Fixing roberta for slow-fast tests
* WIP getting equivalence on pipelines
* slow-to-fast equivalence - working on question-answering pipeline
* optional FAISS tests
* Pipeline Q&A
* Move pipeline tests to their own test job again
* update tokenizer to add sequence id methods
* update to tokenizers 0.9.4
* set sentencepiecce as optional
* clean up squad
* clean up pipelines to use sequence_ids
* style/quality
* wording
* Switch to use_fast = True by default
* update tests for use_fast at True by default
* fix rag tokenizer test
* removing protobuf from required dependencies
* fix NER test for use_fast = True by default
* fixing example tests (Q&A examples use slow tokenizers for now)
* protobuf in main deps extras["sentencepiece"] and example deps
* fix protobug install test
* try to fix seq2seq by switching to slow tokenizers for now
* Update src/transformers/tokenization_utils_base.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Update src/transformers/tokenization_utils_base.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Update some tests
* Small update
* Apply style
* Use max_position_embeddings
* Create a fake attribute
* Create a fake attribute
* Update wrong name
* Wrong TransfoXL model file
* Keep the common tests agnostic
* Update deploy-docs dependencies on CI to enable Flax
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Added pair of ""
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* First addition of Flax/Jax documentation
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* make style
* Ensure input order match between Bert & Roberta
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Install dependencies "all" when building doc
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* wraps build_doc deps with ""
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Addressing @sgugger comments.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Use list to highlight JAX features.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Make style.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Let's not look to much into the future for now.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Style
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
* Create modeling_tf_dpr.py
* Add TFDPR
* Add back TFPegasus, TFMarian, TFMBart, TFBlenderBot
last commit accidentally deleted these 4 lines, so I recover them back
* Add TFDPR
* Add TFDPR
* clean up some comments, add TF input-style doc string
* Add TFDPR
* Make return_dict=False as default
* Fix return_dict bug (in .from_pretrained)
* Add get_input_embeddings()
* Create test_modeling_tf_dpr.py
The current version is already passed all 27 tests!
Please see the test run at :
https://colab.research.google.com/drive/1czS_m9zy5k-iSJbzA_DP1k1xAAC_sdkf?usp=sharing
* fix quality
* delete init weights
* run fix copies
* fix repo consis
* del config_class, load_tf_weights
They shoud be 'pytorch only'
* add config_class back
after removing it, test failed ... so totally only removing "use_tf_weights = None" on Lysandre suggestion
* newline after .. note::
* import tf, np (Necessary for ModelIntegrationTest)
* slow_test from_pretrained with from_pt=True
At the moment we don't have TF weights (since we don't have official official TF model)
Previously, I did not run slow test, so I missed this bug
* Add simple TFDPRModelIntegrationTest
Note that this is just a test that TF and Pytorch gives approx. the same output.
However, I could not test with the official DPR repo's output yet
* upload correct tf model
* remove position_ids as missing keys
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: patrickvonplaten <patrick@huggingface.co>
The new run_ner.py script tries to run prediction on the input
test set `datasets["test"]`, but it should be the tokenized set
`tokenized_datasets["test"]`
* Add next sentence prediction loss computation
* Apply style
* Fix tests
* Add forgotten import
* Add forgotten import
* Use a new parameter
* Remove kwargs and use positional arguments
