* [bug fix] fixed the bug that the actual batch_size is inconsistent with the parameter settings
* reformat
* reformat
* reformat
* add support for dict and BatchEncoding
* add support for dict and BatchEncoding
* add documentation for DataCollatorForNextSentencePrediction
* Some more nits for the docstring
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Some more nits for the docstring
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Some more nits for the docstring
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Some more nits for the docstring
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Some more nits for the docstring
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* rename variables
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* added rag WIP
* path fix
* Formatting / renaming prior to actual work
* added rag WIP
* path fix
* Formatting / renaming prior to actual work
* added rag WIP
* path fix
* Formatting / renaming prior to actual work
* added rag WIP
* Formatting / renaming prior to actual work
* First commit
* improve comments
* Retrieval evaluation scripts
* refactor to include modeling outputs + MPI retriever
* Fix rag-token model + refactor
* Various fixes + finetuning logic
* use_bos fix
* Retrieval refactor
* Finetuning refactoring and cleanup
* Add documentation and cleanup
* Remove set_up_rag_env.sh file
* Fix retrieval wit HF index
* Fix import errors
* Fix quality errors
* Refactor as per suggestions in https://github.com/huggingface/transformers/pull/6813#issuecomment-687208867
* fix quality
* Fix RAG Sequence generation
* minor cleanup plus initial tests
* fix test
* fix tests 2
* Comments fix
* post-merge fixes
* Improve readme + post-rebase refactor
* Extra dependencied for tests
* Fix tests
* Fix tests 2
* Refactor test requirements
* Fix tests 3
* Post-rebase refactor
* rename nlp->datasets
* RAG integration tests
* add tokenizer to slow integration test and allow retriever to run on cpu
* add tests; fix position ids warning
* change structure
* change structure
* add from encoder generator
* save working solution
* make all integration tests pass
* add RagTokenizer.save/from_pretrained and RagRetriever.save/from_pretrained
* don't save paths
* delete unnecessary imports
* pass config to AutoTokenizer.from_pretrained for Rag tokenizers
* init wiki_dpr only once
* hardcode legacy index and passages paths (todo: add the right urls)
* finalize config
* finalize retriver api and config api
* LegacyIndex index download refactor
* add dpr to autotokenizer
* make from pretrained more flexible
* fix ragfortokengeneration
* small name changes in tokenizer
* add labels to models
* change default index name
* add retrieval tests
* finish token generate
* align test with previous version and make all tests pass
* add tests
* finalize tests
* implement thoms suggestions
* add first version of test
* make first tests work
* make retriever platform agnostic
* naming
* style
* add legacy index URL
* docstrings + simple retrieval test for distributed
* clean model api
* add doc_ids to retriever's outputs
* fix retrieval tests
* finish model outputs
* finalize model api
* fix generate problem for rag
* fix generate for other modles
* fix some tests
* save intermediate
* set generate to default
* big refactor generate
* delete rag_api
* correct pip faiss install
* fix auto tokenization test
* fix faiss install
* fix test
* move the distributed logic to examples
* model page
* docs
* finish tests
* fix dependencies
* fix import in __init__
* Refactor eval_rag and finetune scripts
* start docstring
* add psutil to test
* fix tf test
* move require torch to top
* fix retrieval test
* align naming
* finish automodel
* fix repo consistency
* test ragtokenizer save/load
* add rag model output docs
* fix ragtokenizer save/load from pretrained
* fix tokenizer dir
* remove torch in retrieval
* fix docs
* fixe finetune scripts
* finish model docs
* finish docs
* remove auto model for now
* add require torch
* remove solved todos
* integrate sylvains suggestions
* sams comments
* correct mistake on purpose
* improve README
* Add generation test cases
* fix rag token
* clean token generate
* fix test
* add note to test
* fix attention mask
* add t5 test for rag
* Fix handling prefix in finetune.py
* don't overwrite index_name
Co-authored-by: Patrick Lewis <plewis@fb.com>
Co-authored-by: Aleksandra Piktus <piktus@devfair0141.h2.fair>
Co-authored-by: Aleksandra Piktus <piktus@learnfair5102.h2.fair>
Co-authored-by: Aleksandra Piktus <piktus@learnfair5067.h2.fair>
Co-authored-by: Your Name <you@example.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Quentin Lhoest <lhoest.q@gmail.com>
* Copy code from Bert to Roberta and add safeguard script
* Fix docstring
* Comment code
* Formatting
* Update src/transformers/modeling_roberta.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Add test and fix bugs
* Fix style and make new comand
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* fix USE_CUDA, add pipeline
* USE_CUDA fix
* recode SinusoidalPositionalEmbedding into nn.Embedding subclass
was needed for torchscript to work - this is now part of the state_dict, so will have to remove these keys during save_pretrained
* back out (ci debug)
* restore
* slow last?
* facilitate not saving certain keys and test
* remove no longer used keys
* style
* fix logging import
* cleanup
* Update src/transformers/modeling_utils.py
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>
* fix bug in max_positional_embeddings
* rename keys to keys_to_never_save per suggestion, improve the setup
* Update src/transformers/modeling_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Two new pre-trained models "vinai/bertweet-covid19-base-cased" and "vinai/bertweet-covid19-base-uncased" are resulted by further pre-training the pre-trained model "vinai/bertweet-base" on a corpus of 23M COVID-19 English Tweets for 40 epochs.
* Add BERTweet and PhoBERT models
* Update modeling_auto.py
Re-add `bart` to LM_MAPPING
* Update tokenization_auto.py
Re-add `from .configuration_mobilebert import MobileBertConfig`
not sure why it's replaced by `from transformers.configuration_mobilebert import MobileBertConfig`
* Add BERTweet and PhoBERT to pretrained_models.rst
* Update tokenization_auto.py
Remove BertweetTokenizer and PhobertTokenizer out of tokenization_auto.py (they are currently not supported by AutoTokenizer.
* Update BertweetTokenizer - without nltk
* Update model card for BERTweet
* PhoBERT - with Auto mode - without import fastBPE
* PhoBERT - with Auto mode - without import fastBPE
* BERTweet - with Auto mode - without import fastBPE
* Add PhoBERT and BERTweet to TF modeling auto
* Improve Docstrings for PhobertTokenizer and BertweetTokenizer
* Update PhoBERT and BERTweet model cards
* Fixed a merge conflict in tokenization_auto
* Used black to reformat BERTweet- and PhoBERT-related files
* Used isort to reformat BERTweet- and PhoBERT-related files
* Reformatted BERTweet- and PhoBERT-related files based on flake8
* Updated test files
* Updated test files
* Updated tf test files
* Updated tf test files
* Updated tf test files
* Updated tf test files
* Update commits from huggingface
* Delete unnecessary files
* Add tokenizers to auto and init files
* Add test files for tokenizers
* Revised model cards
* Update save_vocabulary function in BertweetTokenizer and PhobertTokenizer and test files
* Revised test files
* Update orders of Phobert and Bertweet tokenizers in auto tokenization file
