GitLab

* docs(wandb): explain how to use W&B integration

fix #5262

* Also mention TensorBoard
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

[Reformer classification head] Implement the reformer model classification head for text classification (#5198)

* Reformer model head classification implementation for text classification

* Reformat the reformer model classification code

* PR review comments, and test case implementation for reformer for classification head changes

* CI/CD reformer for classification head test import error fix

* CI/CD test case implementation  added ReformerForSequenceClassification to all_model_classes

* Code formatting- fixed

* Normal test cases added for reformer classification head

* Fix test cases implementation for the reformer classification head

* removed token_type_id parameter from the reformer classification head

* fixed the test case for reformer classification head

* merge conflict with master fixed

* merge conflict, changed reformer classification to accept the choice_label parameter added in latest code

* refactored the the reformer classification head test code

* reformer classification head, common transform test cases fixed

* final set of the review comment, rearranging the reformer classes and docstring add to classification forward method

* fixed the compilation error and text case fix for reformer classification head

* Apply suggestions from code review

Remove unnecessary dup
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

Minor doc fix.

* implement FlaubertForTokenClassification as a subclass of XLMForTokenClassification

* fix mapping order

* add the doc

* add common tests

* fix longformer global attention output

* fix multi gpu problem

* replace -10000 with 0

* better comment

* make attention output equal local and global

* Update src/transformers/modeling_longformer.py

* Fix Trainer in DataParallel setting

* Fix typo
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

Added general description, information about the tags and also some example usage code.

* Add model type check for pipelines

* Add model type check for pipelines

* rename func

* Fix the init parameters

* Fix format

* rollback unnecessary refactor

* Add Microsoft's CodeBERT

* link style

* single modal

* unused import

* Document model outputs

* Update docs/source/main_classes/output.rst
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

Co-Authored-By: Suraj Patil <surajp815@gmail.com>
Co-Authored-By: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update README.md

* Update README.md

Fixed use of memories in XLNet (caching for language generation + warning when loading improper memoryless model) (#5632)

* Pytorch gpu => cpu proper device

* Memoryless XLNet warning + fixed memories during generation

* Revert "Pytorch gpu => cpu proper device"

This reverts commit 93489b36

* made black happy

* TF generation with memories

* dim => axis

* added padding_text to TF XL models

* Added comment, added TF

Create model card for T5-small fine-tuned on SQUAD v2

Model card for sentence-transformers/bert-base-nli-cls-token

Model card for sentence-transformers/bert-base-nli-max-tokens

* [WIP] Proposal for model outputs

* All Bert models

* Make CI green maybe?

* Fix ONNX test

* Isolate ModelOutput from pt and tf

* Formatting

* Add Electra models

* Auto-generate docstrings from outputs

* Add TF outputs

* Add some BERT models

* Revert TF side

* Remove last traces of TF changes

* Fail with a clear error message

* Add Albert and work through Bart

* Add CTRL and DistilBert

* Formatting

* Progress on Bart

* Renames and finish Bart

* Formatting

* Fix last test

* Add DPR

* Finish Electra and add FlauBERT

* Add GPT2

* Add Longformer

* Add MMBT

* Add MobileBert

* Add GPT

* Formatting

* Add Reformer

* Add Roberta

* Add T5

* Add Transformer XL

* Fix test

* Add XLM + fix XLMForTokenClassification

* Style + XLMRoberta

* Add XLNet

* Formatting

* Add doc of return_tuple arg

* Update PretrainedConfig doc

* Formatting

* Small fixes

* Forgotten args and more cleanup

cc @yjernite

(hotlinking to image works on GitHub but not on external sites)

cc @bashartalafha

* Pytorch gpu => cpu proper device

* Memoryless XLNet warning + fixed memories during generation

* Revert "Memoryless XLNet warning + fixed memories during generation"

This reverts commit 3d3251ff

* Took the operations on the generated_sequence out of the ensure_device scope