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* Create README.md

* Update README.md

* Create README.md

Telugu BERTU Readme file

* Update model_cards/kuppuluri/telugu_bertu/README.md
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* model details

* Apply suggestions from code review
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Model card: CodeBERT fine-tuned for Insecure Code Detection

* Update model_cards/mrm8488/codebert-base-finetuned-detect-insecure-code/README.md
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* use decorator

* remove hardcoded paths

* make the test use more data and do real quality tests

* shave off 10 secs

* add --eval_beams 2, reformat

* reduce train size, use smaller custom dataset

Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* Make Trainer evaluation handle dynamic seq_length

* Document behavior.

* Fix test

* Better fix

* Fixes for realsies this time

* Address review comments

* Without forgetting to save...

* Output global_attentions in Longformer models

* make style

* small refactoring

* fix tests

* make fix-copies

* add for tf as well

* remove comments in test

* make fix-copies

* make style

* add docs

* make docstring pretty
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>

* change TokenClassificationTask class methods to static methods

Since we do not require self in the class methods of TokenClassificationTask we should probably switch to static methods. Also, since the class TokenClassificationTask does not contain a constructor it is currently unusable as is. By switching to static methods this fixes the issue of having to document the intent of the broken class.

Also, since the get_labels and read_examples_from_file methods are ought to be implemented. Static method definitions are unchanged even after inheritance, which means that it can be overridden, similar to other class methods.

* Trigger Build
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* Create README.md

* Update README.md

* Apply suggestions from code review
Co-authored-by: Kevin Canwen Xu <canwenxu@126.com>
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Clean up data collators and datasets

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Remove needless clone
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Try -j option

* Try other thing

* Bigger machine

* Test lower sphinx version

* Remove trailing space

* adding model cards for distil models

* forgot the languages

- The issue is that with previous code we would have the following:

```python
qa_pipeline = (...)
qa_pipeline(question="Where was he born ?", context="")
-> IndexError: Dimension out of range (expected to be in range of [-1, 0], but got 1)
```

The goal here is to improve this to actually return a ValueError
wherever possible.

While at it, I tried to simplify QuestionArgumentHandler's code to
make it smaller and more compat while keeping backward compat.

* update deepset/roberta-base-squad2 to v2

* Update model_cards/deepset/roberta-base-squad2/README.md
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* fix greedy generate test

* delet ipdb

Fixing:

```
src/transformers/tokenization_blenderbot.py:163: DeprecationWarning: invalid escape sequence \s
    token = re.sub("\s{2,}", " ", token)
```

* Bug fix: NER pipeline shouldn't group separate entities of same type

* style fix

* [Bug Fix] Shouldn't group entities that are both 'B' even if they are same type
	(B-type1 B-type1) != (B-type1 I-type1)
[Bug Fix] add an option `ignore_subwords` to ignore subsequent ##wordpieces in predictions. Because some models train on only the first token of a word and not on the subsequent wordpieces (BERT NER default). So it makes sense doing the same thing at inference time.
	The simplest fix is to just group the subwords with the first wordpiece.
	[TODO] how to handle ignored scores? just set them to 0 and calculate zero invariant mean ?
	[TODO] handle different wordpiece_prefix ## ? possible approaches:
		get it from tokenizer? but currently most tokenizers dont have a wordpiece_prefix property?
		have an _is_subword(token)
[Feature add] added option to `skip_special_tokens`. Cause It was harder to remove them after grouping.
[Additional Changes] remove B/I prefix on returned grouped_entities
[Feature Request/TODO] Return indexes?
[Bug TODO]  can't use fast tokenizer with grouped_entities ('BertTokenizerFast' object has no attribute 'convert_tokens_to_string')

* use offset_mapping to fix [UNK] token problem

* ignore score for subwords

* modify ner_pipeline test

* modify ner_pipeline test

* modify ner_pipeline test

* ner_pipeline change ignore_subwords default to true

* add ner_pipeline ignore_subword=False test case

* fix offset_mapping index

* fix style again duh

* change is_subword and convert_tokens_to_string logic

* merge tests with new test structure

* change test names

* remove old tests

* ner tests for fast tokenizer

* fast tokenizers have convert_tokens_to_string

* Fix the incorrect merge
Co-authored-by: Ceyda Cinarel <snu-ceyda@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* make it possible to invoke testconf.py in both test suites without crashing on having the same option added

* perl -pi -e 's|--make_reports|--make-reports|' to be consistent with other opts

* add `pytest --make-reports` to all CIs (and artifacts)

* fix

* Add DataCollatorForTokenClassification and clean tests

* Make quality

* improve documentation of training_args.py

- do_train
- do_eval
- do_predict

* fix line too long

* fix style with black on training_args.py

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

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

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

* fix line length with utils/style_doc

* black reformatting
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>