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(cherry picked from commit b5f2dc5d627d44b8cbb0ccf8ad2b46bea211a236)

The first model added to the repo

Introduce tqdm_enabled parameter on squad_convert_examples_to_features() default to True and set to False in QA pipelines.

* Add qas_id

* Fix incorrect name in squad.py

* Make output files optional for squad eval

* remove max_length = tokenizer.max_length when encoding

* make style

* exbert links for my albert model cards

* Added exbert tag to the metadata block

* Adding "how to cite"

* First pass on utility classes and python tokenizers

* finishing cleanup pass

* style and quality

* Fix tests

* Updating following @mfuntowicz comment

* style and quality

* Fix Roberta

* fix batch_size/seq_length inBatchEncoding

* add alignement methods + tests

* Fix OpenAI and Transfo-XL tokenizers

* adding trim_offsets=True default for GPT2 et RoBERTa

* style and quality

* fix tests

* add_prefix_space in roberta

* bump up tokenizers to rc7

* style

* unfortunately tensorfow does like these - removing shape/seq_len for now

* Update src/transformers/tokenization_utils.py
Co-Authored-By: Stefan Schweter <stefan@schweter.it>

* Adding doc and docstrings

* making flake8 happy
Co-authored-by: Stefan Schweter <stefan@schweter.it>

see https://github.com/huggingface/transformers/pull/3836

* better config serialization

* finish configuration utils

* XLM tokenizer should encode with bos token

* Update tests

* Add support for the null answer in `QuestionAnsweringPipeline`

* black

* Fix min null score computation

* Fix a PR comment

token_type_id is converted into the segment embedding. For question answering,
this needs to highlight whether a token belongs to sequence 0 or 1.
encode_plus takes care of correctly setting this parameter automatically.

* Add TFAlbertForQuestionAnswering

* Add TFRobertaForQuestionAnswering

* Update TFAutoModel with Roberta/Albert for QA

* Clean `super` TF Albert calls

renames `run_bart_sum.py` to `finetune.py`

Changing from "fine-grained token-leven" to "fine-grained token-level"

* Refactored use of newstest2013 to newstest2014. Fixed bug where argparse consumed first command line argument as model_size argument rather than using default model_size by forcing explicit --model_size flag inclusion

* More pythonic file handling through 'with' context

* COSMETIC - ran Black and isort

* Fixed reference to number of lines in newstest2014

* Fixed failing test. More pythonic file handling

* finish PR from tholiao

* remove outcommented lines

* make style

* make isort happy
Co-authored-by: Thomas Liao <tholiao@gmail.com>

* correct gpt2 test inputs

* make style

* delete modeling_gpt2 change in test file

* translate from pytorch

* correct tests

* fix conflicts

* fix conflicts

* fix conflicts

* fix conflicts

* make tensorflow t5 caching work

* make style

* clean reorder cache

* remove unnecessary spaces

* fix test

* Delete some copy pasted code

* add dialoGPT

* update README.md

* fix conflict

* update readme

* add code links to docs

* Update README.md

* Update dialo_gpt2.rst

* Update pretrained_models.rst

* Update docs/source/model_doc/dialo_gpt2.rst
Co-Authored-By: Julien Chaumond <chaumond@gmail.com>

* change filename of dialogpt
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

- adds pytorch-lightning dependency

* remove output_past from pt

* make style

* add optional input length for gpt2

* add use cache to prepare input

* save memory in gpt2

* correct gpt2 test inputs

* make past input optional for gpt2

* finish use_cache for all models

* make style

* delete modeling_gpt2 change in test file

* correct docstring

* correct is true statements for gpt2

* Shifting labels inside TransfoXLLMHead

* Changed doc to reflect change

* Updated pytorch test

* removed IDE whitespace changes

* black reformat
Co-authored-by: TevenLeScao <teven.lescao@gmail.com>