* 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>
* 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.
For the tutorial of "How to generate text", the URL link was wrong (it was linked to the tutorial of "How to train a language model").
I fixed the URL.
* Added transformers-pytorch-cpu and gpu Docker images
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Added automatic jupyter launch for Docker image.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Move image from alpine to Ubuntu to align with NVidia container images.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Added TRANSFORMERS_VERSION argument to Dockerfile.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Added Pytorch-GPU based Docker image
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Added Tensorflow images.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Use python 3.7 as Tensorflow doesnt provide 3.8 compatible wheel.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Remove double FROM instructions on transformers-pytorch-cpu image.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Added transformers-tensorflow-gpu Docker image.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* use the correct ubuntu version for tensorflow-gpu
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Added pipelines example notebook
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Added transformers-cpu and transformers-gpu (including both PyTorch and TensorFlow) images.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Docker images doesnt start jupyter notebook by default.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Tokenizers notebook
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Update images links
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Update Docker images to python 3.7.6 and transformers 2.5.1
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Added 02-transformers notebook.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Trying to realign 02-transformers notebook ?
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Added Transformer image schema
* Some tweaks on tokenizers notebook
* Removed old notebooks.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Attempt to provide table of content for each notebooks
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Second attempt.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Reintroduce transformer image.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Keep trying
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* It's going to fly !
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Remaining of the Table of Content
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Fix inlined elements for the table of content
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Removed anaconda dependencies for Docker images.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Removing notebooks ToC
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Added LABEL to each docker image.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Removed old Dockerfile
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Directly use the context and include transformers from here.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Reduce overall size of compiled Docker images.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Install jupyter by default and use CMD for easier launching of the images.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Reduce number of layers in the images.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Added README.md for notebooks.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Fix notebooks link in README
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Fix some wording issues.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Added blog notebooks too.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Addressing spelling errors in review comments.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
Co-authored-by: MOI Anthony <xn1t0x@gmail.com>
