GitLab

* Create self-hosted.yml

* Update self-hosted.yml

* Update self-hosted.yml

* Update self-hosted.yml

* Update self-hosted.yml

* Update self-hosted.yml

* do not run slow tests, for now

* [ci] For comparison with circleci, let's also run CPU-tests

* [ci] reorganize

* clearer filenames

* [ci] Final tweaks before merging

* rm slow tests on circle ci

* Trigger CI

* On GPU this concurrency was way too high

* changes to allow for tpu training

* black

* tpu

* tpu

* * Added support for Albert when fine-tuning for NER

* Added support for Albert in NER pipeline

* Added command-line options to examples/ner/run_ner.py to better control tokenization

* Added class AlbertForTokenClassification

* Changed output for NerPipeline to use .convert_ids_to_tokens(...) instead of .decode(...) to better reflect tokens

* Added ,

* Now passes style guide enforcement

* Changes from reviews.

* Code now passes style enforcement

* Added test for AlbertForTokenClassification

* Added test for AlbertForTokenClassification

* fix issue and add some tests

* fix issue and add some tests

* updated doc string gpt2

* Fix tests on GPU (torch)

* Fix bart slow tests
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* All Tokenizers

BertTokenizer + few fixes
RobertaTokenizer
OpenAIGPTTokenizer + Fixes
GPT2Tokenizer + fixes
TransfoXLTokenizer
Correct rst for TransformerXL
XLMTokenizer + fixes
XLNet Tokenizer + Style
DistilBERT + Fix XLNet RST
CTRLTokenizer
CamemBERT Tokenizer
FlaubertTokenizer
XLMRobertaTokenizer
cleanup

* cleanup

* add first files

* add xlm roberta integration tests

* make style

* flake 8 issues solved

* change masking to direct labelings

* fix black

* switch to ignore index

* .

* fix black

* Usage: Sequence Classification & Question Answering

* Pipeline example

* Language modeling

* TensorFlow code for Sequence classification

* Custom TF/PT toggler in docs

* QA + LM for TensorFlow

* Finish Usage for both PyTorch and TensorFlow

* Addressing Julien's comments

* More assertive

* cleanup

* Favicon
- added favicon option in conf.py along with the favicon image
- udpated 🤗

 logo. slightly smaller and should appear more consistent across editing programs (no more tongue on the outside of the mouth)
Co-authored-by: joshchagani <joshua@joshuachagani.com>

* Renamed file generate by tokenizers when calling save_pretrained to match python.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Added save_vocabulary tests.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Remove python quick and dirty fix for clean Rust impl.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Bump tokenizers dependency to 0.5.1
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* TransfoXLTokenizerFast uses a json vocabulary file + warning about incompatibility between Python and Rust
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Added some save_pretrained / from_pretrained unittests.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Update tokenizers to 0.5.2
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Quality and format.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* flake8
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Making sure there is really a bug in unittest

* Fix TransfoXL constructor vocab_file / pretrained_vocab_file mixin.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* add explaining example to XLNet LM modeling

* improve docstring for xlnet

Add preprocessing step for transfo-xl tokenization to avoid tokenizing words followed by punction to <unk> (#2987)

* add preprocessing to add space before punctuation for transfo_xl

* improve warning messages

* make style

* compile regex at instantination of tokenizer object

* Add disable_outgoing to pretrained items

Setting disable_outgoing=True disables outgonig traffic:
- etags are not looked up
- models are not downloaded

* parameter name change

* Remove forgotten print

* Testing that encode_plus and batch_encode_plus behave the same way

Spoiler alert: they don't

* Testing rest of arguments in batch_encode_plus

* Test tensor return in batch_encode_plus

* Addressing Sam's comments

* flake8

* Simplified with `num_added_tokens`

* add slow generate lm_model tests

* fix conflicts

* merge conflicts

* fix conflicts

* add slow generate lm_model tests

* make style

* delete unused variable

* fix conflicts

* fix conflicts

* fix conflicts

* delete unused variable

* fix conflicts

* finished hard coded tests

Warning on `add_special_tokens` when passed to `encode`, `encode_plus` and `batch_encode_plus`

* Added support for Albert in NER pipeline

* Added command-line options to examples/ner/run_ner.py to better control tokenization

* Added class AlbertForTokenClassification

* Changed output for NerPipeline to use .convert_ids_to_tokens(...) instead of .decode(...) to better reflect tokens