GitLab

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>

* added qg evaluation notebook

* Update notebooks/README.md
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* 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

* Update ONNX notebook to include section on quantization.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Addressing ONNX team comments

Co-authored-by: eliska <3648991+elisans@users.noreply.github.com>

Signed-off-by: lordtt13 <thakurtanmay72@yahoo.com>

* Créé avec Colaboratory

* delete old file

* tf_train

* adapt timing for tpu

* fix timing

* fix timing

* fix timing

* fix timing

* update notebook

* add tests

* Add Reformer MLM notebook

* Update notebooks/README.md

* first doc version

* add benchmark docs

* fix typos

* improve README

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

* fix naming and docs
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* remove references to old API in docstring - update data processors

* style

* fix tests - better type checking error messages

* better type checking

* include awesome fix by @LysandreJik for #5310

* updated doc and examples

* add notebook

* Créé avec Colaboratory

* move notebook to correct folder

* correct link

* correct filename

* correct filename

* better name

* 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>

* Add missing arg when creating model

* Fix typos

* Remove from_tf flag when creating model

* 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>

* fix longformer model names in examples

* a better name for the notebook

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

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

* adding BART summarization how-to community notebook

* Update notebooks/README.md
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* add T5 fine-tuning notebook [Community notebooks]

* Update README.md
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Adding optimizations block from ONNXRuntime.

* Turn off external data format by default for PyTorch export.

* Correct the way use_external_format is passed through the cmdline args.

* Update README.md

* Update README.md

* Update README.md

* Update README.md