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* Create README.md

* Update model_cards/ncoop57/bart-base-code-summarizer-java-v0/README.md
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* configuration_squeezebert.py

thin wrapper around bert tokenizer

fix typos

wip sb model code

wip modeling_squeezebert.py. Next step is to get the multi-layer-output interface working

set up squeezebert to use BertModelOutput when returning results.

squeezebert documentation

formatting

allow head mask that is an array of [None, ..., None]

docs

docs cont'd

path to vocab

docs and pointers to cloud files (WIP)

line length and indentation

squeezebert model cards

formatting of model cards

untrack modeling_squeezebert_scratchpad.py

update aws paths to vocab and config files

get rid of stub of NSP code, and advise users to pretrain with mlm only

fix rebase issues

redo rebase of modeling_auto.py

fix issues with code formatting

more code format auto-fixes

move squeezebert before bert in tokenization_auto.py and modeling_auto.py because squeezebert inherits from bert

tests for squeezebert modeling and tokenization

fix typo

move squeezebert before bert in modeling_auto.py to fix inheritance problem

disable test_head_masking, since squeezebert doesn't yet implement head masking

fix issues exposed by the test_modeling_squeezebert.py

fix an issue exposed by test_tokenization_squeezebert.py

fix issue exposed by test_modeling_squeezebert.py

auto generated code style improvement

issue that we inherited from modeling_xxx.py: SqueezeBertForMaskedLM.forward() calls self.cls(), but there is no self.cls, and I think the goal was actually to call self.lm_head()

update copyright

resolve failing 'test_hidden_states_output' and remove unused encoder_hidden_states and encoder_attention_mask

docs

add integration test. rename squeezebert-mnli --> squeezebert/squeezebert-mnli

autogenerated formatting tweaks

integrate feedback from patrickvonplaten and sgugger to programming style and documentation strings

* tiny change to order of imports

* Create README.md

* language metadata
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

Model now fine-tuned on Transformers 3.1.0, previous out-of-date model was fine-tuned on Transformers 2.3.0.

Model card for akhooli/personachat-arabic

* Creating readme for bert-base-mongolian-cased

* Update model_cards/bayartsogt/bert-base-mongolian-cased/README.md
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Add DeBERTa model

* Remove dependency of deberta

* Address comments

* Patch DeBERTa
Documentation
Style

* Add final tests

* Style

* Enable tests + nitpicks

* position IDs

* BERT -> DeBERTa

* Quality

* Style

* Tokenization

* Last updates.

* @patrickvonplaten's comments

* Not everything can be a copy

* Apply most of @sgugger's review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Last reviews

* DeBERTa -> Deberta
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Hi, just corrected the example code, add 2 links and fixed some typos

* Create README.md

MagBERT-NER : Added widget (Text)

* Rename model_cards/README.md to model_cards/TypicaAI/magbert-ner/README.md

Add links to models fine-tuned on a downstream task

The score for the F1 metric was reported as the Exact Match and vice-versa.

* Added RobBERT-v2 model card

* minor Tweaks
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

This PR includes the model card for the IXAmBERT model which has been recently uploaded to the huggingface repository.

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

We use ISO 639-1 cc @gentaiscool