- 17 Sep, 2020 1 commit
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Dhaval Taunk authored
* added multilabel classification using distilbert notebook to community notebooks * added multilabel classification using distilbert notebook to community notebooks
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- 08 Sep, 2020 1 commit
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Philipp Schmid authored
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- 08 Aug, 2020 1 commit
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elsanns authored
Co-authored-by:eliska <3648991+elisans@users.noreply.github.com>
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- 28 Jul, 2020 1 commit
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Tanmay Thakur authored
Signed-off-by:lordtt13 <thakurtanmay72@yahoo.com>
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- 10 Jul, 2020 1 commit
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Patrick von Platen authored
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- 01 Jul, 2020 1 commit
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Patrick von Platen authored
* Add Reformer MLM notebook * Update notebooks/README.md
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- 26 Jun, 2020 1 commit
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Patrick von Platen authored
* add notebook * Cr茅茅 avec Colaboratory * move notebook to correct folder * correct link * correct filename * correct filename * better name
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- 24 Jun, 2020 1 commit
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Sylvain Gugger authored
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- 22 Jun, 2020 1 commit
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Micha毛l Benesty authored
* Add link to new comunity notebook (optimization) related to https://github.com/huggingface/transformers/issues/4842#event-3469184635 This notebook is about benchmarking model training with/without dynamic padding optimization. https://github.com/ELS-RD/transformers-notebook Using dynamic padding on MNLI provides a **4.7 times training time reduction**, with max pad length set to 512. The effect is strong because few examples are >> 400 tokens in this dataset. IRL, it will depend of the dataset, but it always bring improvement and, after more than 20 experiments listed in this [article](https://towardsdatascience.com/divide-hugging-face-transformers-training-time-by-2-or-more-21bf7129db9q-21bf7129db9e?source=friends_link&sk=10a45a0ace94b3255643d81b6475f409 ), it seems to not hurt performance. Following advice from @patrickvonplaten I do the PR myself :-) * Update notebooks/README.md Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com>
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- 03 Jun, 2020 1 commit
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Abhishek Kumar Mishra authored
* 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:
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- 02 Jun, 2020 1 commit
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Lorenzo Ampil authored
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- 29 May, 2020 2 commits
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Patrick von Platen authored
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Iz Beltagy authored
* fix longformer model names in examples * a better name for the notebook
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- 28 May, 2020 3 commits
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Iz Beltagy authored
Co-authored-by: -
Suraj Patil authored
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Lavanya Shukla authored
Co-authored-by:
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- 26 May, 2020 1 commit
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ohmeow authored
* adding BART summarization how-to community notebook * Update notebooks/README.md Co-authored-by:
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- 22 May, 2020 2 commits
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Patrick von Platen authored
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Patrick von Platen authored
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- 20 May, 2020 1 commit
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Nathan Cooper authored
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- 19 May, 2020 1 commit
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Suraj Patil authored
* add T5 fine-tuning notebook [Community notebooks] * Update README.md Co-authored-by:
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- 18 May, 2020 1 commit
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Patrick von Platen authored
* Update README.md * Update README.md * Update README.md * Update README.md
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- 14 May, 2020 2 commits
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Morgan Funtowicz authored
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Funtowicz Morgan authored
* 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.
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- 06 Apr, 2020 1 commit
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Lysandre Debut authored
* Update notebooks * From local to global link * from local links to *actual* global links
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- 19 Mar, 2020 1 commit
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Kyeongpil Kang authored
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.
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- 18 Mar, 2020 1 commit
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Patrick von Platen authored
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- 05 Mar, 2020 2 commits
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Morgan Funtowicz authored
Signed-off-by:Morgan Funtowicz <morgan@huggingface.co>
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Morgan Funtowicz authored
Signed-off-by:
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- 04 Mar, 2020 3 commits
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Morgan Funtowicz authored
Signed-off-by: -
Julien Chaumond authored
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Funtowicz Morgan authored
* Added transformers-pytorch-cpu and gpu Docker images Signed-off-by:
MOI Anthony <xn1t0x@gmail.com>
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