GitLab

* Increase pipeline support for ONNX export.

* Style.

* Make DataCollator a callable

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

* manually set device in trainer args

* check if current device is cuda before set_device

* Explicitly set GPU ID when using single GPU

This addresses https://github.com/huggingface/transformers/issues/4657#issuecomment-642228099

* Create README.md

* Update model_cards/ipuneetrathore/bert-base-cased-finetuned-finBERT/README.md
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* utils_ner: do not add extra sep token for RoBERTa model

* run_pl_ner: do not add extra sep token for RoBERTa model

* [model card] model card for bart-large-finetuned-squadv1

* add metadata link to the dataset

* Improve ONNX export logging to give more information about the generated graph.

* Correctly handle input and output in the logging.

* Update hans data to be able to use Trainer

* Fixes

* Deal with tokenizer that don't have token_ids

* Clean up things

* Simplify data use

* Fix the input dict

* Formatting + proper path in README

see corresponding model pages to see how it's rendered

* Add AlbertForMultipleChoice

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

* first commit

* add new auto models

* better naming

* fix bert automodel

* fix automodel for pretraining

* add models to init

* fix name typo

* fix typo

* better naming

* future warning instead of depreciation warning

* Support multiple choice in tf common model tests

* Add the input_embeds test

* Fixed resize_token_embeddings for transfo_xl model

* Fixed resize_token_embeddings for transfo_xl.

Added custom methods to TransfoXLPreTrainedModel for resizing layers of
the AdaptiveEmbedding.

* Updated docstring

* Fixed resizinhg cutoffs; added check for new size of embedding layer.

* Added test for resize_token_embeddings

* Fixed code quality

* Fixed unchanged cutoffs in model.config
Co-authored-by: Rafael Weingartner <rweingartner.its-b2015@fh-salzburg.ac.at>

* Split LMBert model in two

* Fix example

* Remove lm_labels

* Adapt tests, refactor prepare_for_generation

* Fix merge

* Hide BeartLMHeadModel

* check type before logging to ensure it's a scalar

* log when Trainer attempts to add a non-scalar value using TensorboardX's writer.add_scalar so we know what kinds of fixes are appropriate

* black it

* rephrase log message to clarify attribute was dropped
Co-authored-by: Julien Chaumond <chaumond@gmail.com>
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Run a single wandb instance per TPU run

* wandb: self.is_world_master

* make style
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* 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

* fix doc

* add format file

* add output attentions to all docs

* add also for bart

* fix naming

* re-add doc to config

* Fix CI

* Deal with multiple choice in common tests

* Remove unused arguments

* Formatting

* Remove second todo comment

`is_leaf` may become `False` after `.to(device=device)` function call.