GitLab

* Add index to be returned by NerPipeline to allow for the creation of

* Add entity groups

* Convert entity list to dict

* Add entity to entity_group_disagg atfter updating entity gorups

* Change 'group' parameter to 'grouped_entities'

* Add unit tests for grouped NER pipeline case

* Correct variable name typo for NER_FINETUNED_MODELS

* Sync grouped tests to recent test updates

* Better p_mask building

* Adressing @mfuntowicz comments

* Added generic ONNX conversion script for PyTorch model.

* WIP initial TF support.

* TensorFlow/Keras ONNX export working.

* Print framework version info

* Add possibility to check the model is correctly loading on ONNX runtime.

* Remove quantization option.

* Specify ONNX opset version when exporting.

* Formatting.

* Remove unused imports.

* Make functions more generally reusable from other part of the code.

* isort happy.

* flake happy

* Export only feature-extraction for now

* Correctly check inputs order / filter before export.

* Removed task variable

* Fix invalid args call in load_graph_from_args.

* Fix invalid args call in convert.

* Fix invalid args call in infer_shapes.

* Raise exception and catch in caller function instead of exit.

* Add 04-onnx-export.ipynb notebook

* More WIP on the notebook

* Remove unused imports

* Simplify & remove unused constants.

* Export with constant_folding in PyTorch

* Let's try to put function args in the right order this time ...

* Disable external_data_format temporary

* ONNX notebook draft ready.

* Updated notebooks charts + wording

* Correct error while exporting last chart in notebook.

* Adressing @LysandreJik comment.

* Set ONNX opset to 11 as default value.

* Set opset param mandatory

* Added ONNX export unittests

* Quality.

* flake8 happy

* Add keras2onnx dependency on extras["tf"]

* Pin keras2onnx on github master to v1.6.5

* Second attempt.

* Third attempt.

* Use the right repo URL this time ...

* Do the same for onnxconverter-common

* Added keras2onnx and onnxconveter-common to 1.7.0 to supports TF2.2

* Correct commit hash.

* Addressing PR review: Optimization are enabled by default.

* Addressing PR review: small changes in the notebook

* setup.py comment about keras2onnx versioning.

* fix loss calculation in evaluation

* fix evaluation on TPU when prediction_loss_only is True

* Create README.md

* Update model_cards/savasy/bert-base-turkish-squad/README.md
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

covers torch and tf. Also fixes a failing @slow test

* Fix: unpin flake8 and fix cs errors

* Ok we still need to quote those

see context in https://github.com/huggingface/transformers/pull/4223

Unfortunately i accidentally orphaned my other PR

[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

* Add QA trainer example for TF

* Make data_dir optional

* Fix parameter logic

* Fix feature convert

* Update the READMEs to add the question-answering task

* Apply style

* Change 'sequence-classification' to 'text-classification' and prefix with 'eval' all the metric names

* Apply style

* Apply style

Fix for #3865. PretrainedTokenizer mapped " do not" into " don't" when .decode(...) is called. Removed the " do not" --> " don't" mapping from clean_up_tokenization(...). (#4024)

* Improvements to the wandb integration

* small reorg + no global necessary

* feat(trainer): log epoch and final metrics

* Simplify logging a bit

* Fixup

* Fix crash when just running eval
Co-authored-by: Chris Van Pelt <vanpelt@gmail.com>
Co-authored-by: Boris Dayma <boris.dayma@gmail.com>

* Allow BatchEncoding to be initialized empty.

This is required by recent changes introduced in TF 2.2.

* Attempt to unpin Tensorflow to 2.2 with the previous commit.