GitLab

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

* T5 Model Cards

* Fix paths

* Fix tags

* lang-en

* Attempt to fix the way squad_convert_examples_to_features pad the elements for the QA pipeline.
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>

* Quality
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>

* Make the code easier to read and avoid testing multiple test the same thing.
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>

* missing enum value on truncation_strategy.
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>

* Rethinking for the easiest fix: expose the padding strategy on squad_convert_examples_to_features.
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>

* Remove unused imports.
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>

* Update doc to new model outputs

* Fix outputs in quicktour

Add nlp dataset used

Add dataset used as it is now part of nlp package

* Add ComVE model cards

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

* Created model card for my extreme summarization model

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

* Created model card for my summarization model

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

- Maybe the result of this query answers the question You did some days ago @julien-c ;-)

The DataParallel training was fixed in https://github.com/huggingface/transformers/pull/5733, this commit also fixes the evaluation. It's more convenient when the user enables both `do_train` and `do_eval`.

Huge MT speedup!

* Improve doc of use_cache

* Update src/transformers/configuration_xlnet.py
Co-authored-by: Teven <teven.lescao@gmail.com>
Co-authored-by: Teven <teven.lescao@gmail.com>

* DataParallel fixes:

1. switched to a more precise check
-        if self.args.n_gpu > 1:
+        if isinstance(model, nn.DataParallel):

2. fix tests - require the same fixup under DataParallel as the training module

* another fix