* Add LayoutLMForSequenceClassification and integration tests
Improve docs
Add LayoutLM notebook to list of community notebooks
* Make style & quality
* Address comments by @sgugger, @patrickvonplaten and @LysandreJik
* Fix rebase with master
* Reformat in one line
* Improve code examples as requested by @patrickvonplaten
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* First commit: adding all files from tapas_v3
* Fix multiple bugs including soft dependency and new structure of the library
* Improve testing by adding torch_device to inputs and adding dependency on scatter
* Use Python 3 inheritance rather than Python 2
* First draft model cards of base sized models
* Remove model cards as they are already on the hub
* Fix multiple bugs with integration tests
* All model integration tests pass
* Remove print statement
* Add test for convert_logits_to_predictions method of TapasTokenizer
* Incorporate suggestions by Google authors
* Fix remaining tests
* Change position embeddings sizes to 512 instead of 1024
* Comment out positional embedding sizes
* Update PRETRAINED_VOCAB_FILES_MAP and PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
* Added more model names
* Fix truncation when no max length is specified
* Disable torchscript test
* Make style & make quality
* Quality
* Address CI needs
* Test the Masked LM model
* Fix the masked LM model
* Truncate when overflowing
* More much needed docs improvements
* Fix some URLs
* Some more docs improvements
* Test PyTorch scatter
* Set to slow + minify
* Calm flake8 down
* First commit: adding all files from tapas_v3
* Fix multiple bugs including soft dependency and new structure of the library
* Improve testing by adding torch_device to inputs and adding dependency on scatter
* Use Python 3 inheritance rather than Python 2
* First draft model cards of base sized models
* Remove model cards as they are already on the hub
* Fix multiple bugs with integration tests
* All model integration tests pass
* Remove print statement
* Add test for convert_logits_to_predictions method of TapasTokenizer
* Incorporate suggestions by Google authors
* Fix remaining tests
* Change position embeddings sizes to 512 instead of 1024
* Comment out positional embedding sizes
* Update PRETRAINED_VOCAB_FILES_MAP and PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
* Added more model names
* Fix truncation when no max length is specified
* Disable torchscript test
* Make style & make quality
* Quality
* Address CI needs
* Test the Masked LM model
* Fix the masked LM model
* Truncate when overflowing
* More much needed docs improvements
* Fix some URLs
* Some more docs improvements
* Add add_pooling_layer argument to TapasModel
Fix comments by @sgugger and @patrickvonplaten
* Fix issue in docs + fix style and quality
* Clean up conversion script and add task parameter to TapasConfig
* Revert the task parameter of TapasConfig
Some minor fixes
* Improve conversion script and add test for absolute position embeddings
* Improve conversion script and add test for absolute position embeddings
* Fix bug with reset_position_index_per_cell arg of the conversion cli
* Add notebooks to the examples directory and fix style and quality
* Apply suggestions from code review
* Move from `nielsr/` to `google/` namespace
* Apply Sylvain's comments
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Rogge Niels <niels.rogge@howest.be>
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Looking at the current community notebooks, it seems that few are targeted for absolute beginners and even fewer are written with TensorFlow. This notebook describes absolutely everything a beginner would need to know, including how to save/load their model and use it for new predictions (this is often omitted in tutorials)
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* t5 t5 community notebook added
* author link updated
* t5 t5 community notebook added
* author link updated
* new colab link updated
Co-authored-by: harris <muhammad.harris@visionx.io>
* added multilabel classification using distilbert notebook to community notebooks
* added multilabel classification using distilbert notebook to community notebooks
* Added links to more community notebooks
Added links to 3 more community notebooks from the git repo: https://github.com/abhimishra91/transformers-tutorials
Different Transformers models are fine tuned on Dataset using PyTorch
* Update README.md
* Update README.md
* Update README.md
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
