GitLab

* Update glossary

* Update docs/source/glossary.rst
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Add MobileBert

* Quality + Conversion script

* style

* Update src/transformers/modeling_mobilebert.py

* Links to S3

* Style

* TFMobileBert

Slight fixes to the pytorch MobileBert
Style

* MobileBertForMaskedLM (PT + TF)

* MobileBertForNextSentencePrediction (PT + TF)

* MobileFor{MultipleChoice, TokenClassification} (PT + TF)


ss

* Tests + Auto

* Doc

* Tests

* Addressing @sgugger's comments

* Adressing @patrickvonplaten's comments

* Style

* Style

* Integration test

* style

* Model card
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update installation page and add contributing to the doc

* Remove mention of symlinks

* Reorganize topics and add all models

* add eli5 examples

* add dense query script

* query_di

* merging

* merging

* add_utils

* adds nearest neighbor wikipedia

* batch queries

* training_retriever

* new notebooks

* moved retriever traiing script

* finished wiki40b

* max_len_fix

* train_s2s

* retriever_batch_checkpointing

* cleanup

* merge

* dim_fix

* fix_indexer

* fix_wiki40b_snippets

* fix_embed_for_r

* fp32 index

* fix_sparse_q

* joint_training

* remove obsolete datasets

* add_passage_nn_results

* add_passage_nn_results

* add_batch_nn

* add_batch_nn

* add_data_scripts

* notebook

* notebook

* notebook

* fix_multi_gpu

* add_app

* full_caching

* full_caching

* notebook

* sparse_done

* images

* notebook

* add_image_gif

* with_Gif

* add_contr_image

* notebook

* notebook

* notebook

* train_functions

* notebook

* min_retrieval_length

* pandas_option

* notebook

* min_retrieval_length

* notebook

* notebook

* eval_Retriever

* notebook

* images

* notebook

* add_example

* add_example

* notebook

* fireworks

* notebook

* notebook

* joe's notebook comments

* app_update

* notebook

* notebook_link

* captions

* notebook

* assing RetriBert model

* add RetriBert to Auto

* change AutoLMHead to AutoSeq2Seq

* notebook downloads from hf models

* style_black

* style_black

* app_update

* app_update

* fix_app_update

* style

* style

* isort

* Delete WikiELI5training.ipynb

* Delete evaluate_eli5.py

* Delete WikiELI5explore.ipynb

* Delete ExploreWikiELI5Support.html

* Delete explainlikeimfive.py

* Delete wiki_snippets.py

* children before parent

* children before parent

* style_black

* style_black_only

* isort

* isort_new

* Update src/transformers/modeling_retribert.py
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* typo fixes

* app_without_asset

* cleanup

* Delete ELI5animation.gif

* Delete ELI5contrastive.svg

* Delete ELI5wiki_index.svg

* Delete choco_bis.svg

* Delete fireworks.gif

* Delete huggingface_logo.jpg

* Delete huggingface_logo.svg

* Delete Long_Form_Question_Answering_with_ELI5_and_Wikipedia.ipynb

* Delete eli5_app.py

* Delete eli5_utils.py

* readme

* Update README.md

* unused imports

* moved_info

* default_beam

* ftuned model

* disclaimer

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

* black

* add_doc

* names

* isort_Examples

* isort_Examples

* Add doc to index
Co-authored-by: Julien Chaumond <chaumond@gmail.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* Add `DistilBertForMultipleChoice`

[HUGE] Refactoring tokenizers backend - padding - truncation - pre-tokenized pipeline - fast tokenizers - tests (#4510)

* Use tokenizers pre-tokenized pipeline

* failing pretrokenized test

* Fix is_pretokenized in python

* add pretokenized tests

* style and quality

* better tests for batched pretokenized inputs

* tokenizers clean up - new padding_strategy - split the files

* [HUGE] refactoring tokenizers - padding - truncation - tests

* style and quality

* bump up requied tokenizers version to 0.8.0-rc1

* switched padding/truncation API - simpler better backward compat

* updating tests for custom tokenizers

* style and quality - tests on pad

* fix QA pipeline

* fix backward compatibility for max_length only

* style and quality

* Various cleans up - add verbose

* fix tests

* update docstrings

* Fix tests

* Docs reformatted

* __call__ method documented
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* Add AlbertForMultipleChoice

* Make up to date and add all models to common tests

* ElectraForQuestionAnswering

* udate __init__

* add test for electra qa model

* add ElectraForQuestionAnswering in auto models

* add ElectraForQuestionAnswering in all_model_classes

* fix outputs, input_ids defaults to None

* add ElectraForQuestionAnswering in docs

* remove commented line

* Add XLMRobertaForQuestionAnswering

* Formatting

* Make test happy

* Clean documentation

* Add badges for models and docs

* Add model summary

* Add link to pretrained models

* [hf_api] Attach all unknown attributes for future-proof compatibility

* [Pipeline] NerPipeline is really a TokenClassificationPipeline

* modelcard.py: I don't think we need to force the download

* Remove config, tokenizer from SUPPORTED_TASKS as we're moving to one model = one weight + one tokenizer

* FillMaskPipeline: also output token in string form

* TextClassificationPipeline: option to return all scores, not just the argmax

* Update docs/source/main_classes/pipelines.rst

* 🐛 Fix model ids for BART and Flaubert

* Kill model archive maps

* Fixup

* Also kill model_archive_map for MaskedBertPreTrainedModel

* Unhook config_archive_map

* Tokenizers: align with model id changes

* make style && make quality

* Fix CI

* better api

* improve automatic setting of global attention mask

* fix longformer bug

* fix global attention mask in test

* fix global attn mask flatten

* fix slow tests

* update docstring

* update docs and make more robust

* improve attention mask

* add multiple choice for longformer

* add models to docs

* adapt docstring

* add test to longformer

* add longformer for mc in init and modeling auto

* fix tests

* per_device instead of per_gpu/error thrown when argument unknown

* [docs] Restore examples.md symlink

* Correct absolute links so that symlink to the doc works correctly

* Update src/transformers/hf_argparser.py
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Warning + reorder

* Docs

* Style

* not for squad
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* add new longformer for question answering model

* add new config as well

* fix links

* fix links part 2

* fix reformer num buckets

* fix

* adapt docs

* set num buckets in config

changed from https://https://arxiv.org/abs/2001.04451.pdf to https://arxiv.org/abs/2001.04451.pdf

* add longformer docs

* improve docs

* first commit

* bug fixes

* better examples

* undo padding

* remove wrong VOCAB_FILES_NAMES

* License

* make style

* make isort happy

* unit tests

* integration test

* make `black` happy by undoing `isort` changes!!

* lint

* no need for the padding value

* batch_size not bsz

* remove unused type casting

* seqlen not seq_len

* staticmethod

* `bert` selfattention instead of `n2`

* uint8 instead of bool + lints

* pad inputs_embeds using embeddings not a constant

* black

* unit test with padding

* fix unit tests

* remove redundant unit test

* upload model weights

* resolve todo

* simpler _mask_invalid_locations without lru_cache + backward compatible masked_fill_

* increase unittest coverage

[Marian Fixes] prevent predicting pad_token_id before softmax, support language codes, name multilingual models (#4290)

* add first text for generation

* add generation pipeline to usage

* Created using Colaboratory

* correct docstring

* finish

"Migrating from pytorch-transformers to transformers" is missing in the main document. It is available in the main `readme` thought. Just move it to the document.

* Add ALBERT to convert command of transformers-cli

* Document ALBERT tf to pytorch model conversion

* docs: fix link to token classification (NER) example

* examples: fix links to NER scripts

* adapt convert script

* update convert script

* finish

* fix marian pretrained docs