GitLab

* Add clear description of how to train T5

* correct docstring in T5

* correct typo

* correct docstring format

* update t5 model docs

* implement collins feedback

* fix typo and add more explanation for sentinal tokens

* delete unnecessary todos

* force bleu

* fix wrong file name

* rename file

* different filenames for each example test

* test files should clean up after themselves

* test files should clean up after themselves

* do not force bleu

* correct typo

* fix isort

* Use tokenizer.num_added_tokens to count number of added special_tokens instead of hardcoded numbers.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* run_ner.py - Do not add a label to the labels_ids if word_tokens is empty.

This can happen when using bert-base-multilingual-cased with an input containing an unique space.
In this case, the tokenizer will output just an empty word_tokens thus leading to an non-consistent behavior
over the labels_ids tokens adding one more tokens than tokens vector.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* add t5 docs basis

* improve docs

* add t5 docs

* improve t5 docstring

* add t5 tokenizer docstring

* finish docstring

* make style

* add pretrained models

* correct typo

* make examples work

* finalize docs

T5-small in test


isort

For some reason Sphinx extremely dislikes this and crashes.

* trim seq_len below 1024 if there are columns full of pad_token_id
* Centralize trim_batch so SummarizationDataset can use it too

* Dummy inputs to model.device

* Move self.device to ModuleUtilsMixin

* delete lm_head, skips weight tying
* Fixed s3

* add translation example

* make style

* adapt docstring

* add gpu device as input for example

* small renaming

* better README

* rebase to master

* change tf to pytorch

* change to pytorch

* small fix

* renaming

* add gpu training possibility

* renaming

* improve README

* incoorporate collins feedback

* better Readme

* better README.md

* Add the missing token classification for XLM

* fix styling

* Add XLMForTokenClassification to AutoModelForTokenClassification class

* Fix docstring typo for non-existing class

* Add the missing token classification for XLM

* fix styling

* fix styling

* Add XLMForTokenClassification to AutoModelForTokenClassification class

* Fix docstring typo for non-existing class

* Add missing description for AlbertForTokenClassification

* fix styling

* Add missing docstring for AlBert

* Slow tests should be slow
Co-authored-by: Sakares Saengkaew <s.sakares@gmail.com>
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>

* fix merge conflicts

* add t5 summarization example

* change parameters for t5 summarization

* make style

* add first code snippet for translation

* only add prefixes

* add prefix patterns

* make style

* renaming

* fix conflicts

* remove unused patterns

* solve conflicts

* fix merge conflicts

* remove translation example

* remove summarization example

* make sure tensors are in numpy for float comparsion

* re-add t5 config

* fix t5 import config typo

* make style

* remove unused numpy statements

* update doctstring

* import translation pipeline

* add bert bahasa readme

* update readme

* update readme

* added xlnet

* solve conflicts

* move warnings below

* incorporate changes

* add pad_to_max_length to pipelines

* add bug fix for T5 beam search

* add prefix patterns

* make style

* fix conflicts

* adapt pipelines for task specific parameters

* improve docstring

* remove unused patterns

* add new default configs

* change prefix default to None

* [ci] Also run test_examples in py37

(will revert at the end of the experiment)

* InputExample: use immutable dataclass

* [deps] Install dataclasses for Py<3.7

* [skip ci] Revert "[ci] Also run test_examples in py37"

This reverts commit d29afd9959786b77759b0b8fa4e6b4335b952015.