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Minor changes: Add arxiv link + Layout improvement + fix typos

by @nikkon3

* Initial callback proposal

* Finish various callbacks

* Post-rebase conflicts

* Fix tests

* Don't use something that's not set

* Documentation

* Remove unwanted print.

* Document all models can work

* Add tests + small fixes

* Update docs/source/internal/trainer_utils.rst
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Address review comments

* Fix TF tests

* Real fix this time

* This one should work

* Fix typo

* Really fix typo
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Fix UnboundLocalError when PaddingStrategy is MAX_LENGTH

* Fix UnboundLocalError for TruncationStrategy

Resolves: #7613

* Add GPT2ForSequenceClassification based on DialogRPT

* Better documentation

* Code quality

It should be T5-3B not T5-3M.

- Use cuda:10.2 image instead of 10.1 (to address version mismatch
  warning with pytorch)
- Use devel version that is built on the runtime and includes headers
  and development tools (was otherwise failing to build apex)

* Create README.md

Model description for all LEGAL-BERT models, published as part of  "LEGAL-BERT: The Muppets straight out of Law School". Chalkidis et al., 2018, In Findings of EMNLP 2020

* Update model_cards/nlpaueb/legal-bert-base-uncased/README.md
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Fixing top_k and min_length assertions, and a typo fix

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Configuration

* Modeling

* Tokenization

* Obliterate the trailing spaces

* From underlines to long underlines

* Add ProtT5-XL-BFD model card

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* check only .py files

* better choice of words

* First try

* Fix TF utils

* Handle authorized unexpected keys when loading weights

* Add several more authorized unexpected keys

* Apply style

* Fix test

* Address Patrick's comments.

* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Apply style

* Make return_dict the default behavior and display a warning message

* Revert

* Replace wrong keyword

* Revert code

* Add forgot key

* Fix bug in loading PT models from a TF one.

* Fix sort

* Add a test for custom load weights in BERT

* Apply style

* Remove unused import
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Check and update model list in index.rst automatically

* Check and update model list in index.rst automatically

* Adapt template

* PoC on RAG

* Format class name/obj name

* Better name in message

* PoC on one TF model

* Add PyTorch and TF dummy objects + script

* Treat scikit-learn

* Bad copy pastes

* Typo

'The class `AutoModelWithLMHead` is deprecated and will be removed in a future version. Please use `AutoModelForCausalLM` for causal language models, `AutoModelForMaskedLM` for masked language models and `AutoModelForSeq2SeqLM` for encoder-decoder models.'
I dont know how to change the 'How to use this model directly from the 🤗/transformers library:' part since it is not part of the model-paper

* docs(pretrained_models): fix num parameters

* fix(pretrained_models): correct typo
Co-authored-by: Amin <amin.geotrend@gmail.com>

* fix squad tokenization for roberta & co

* change to pure type based check

* sort imports

* 🚩 Add `power` argument for TF PolynomialDecay

* 🚩 Create default optimizer with power

* 🚩 Add argument to training args

* 🚨 Clean code format

* 🚨 Fix black warning

* 🚨 Fix code format

* 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

* Cleanup documentation for BART, Marian, MBART and Pegasus

* Cleanup documentation for BART, Marian, MBART and Pegasus

* LayoutLM: add exception handling for bbox values

To replicate unhandled error:

- In `test_modelling_layoutlm.py` set `range_bbox=1025`, i.e. greater 1024
- Run `pytest tests/test_modeling_layoutlm.py`

Requirement for bbox values to be within the range 0-1000 is documented
but if it is violated then it isa not clear what is the issue from error
message.

* Update src/transformers/modeling_layoutlm.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>