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* Pad to 8x for fp16 multiple choice example (#9752) * Pad to 8x for fp16 squad trainer example (#9752) * Pad to 8x for fp16 ner example (#9752) * Pad to 8x for fp16 swag example (#9752) * Pad to 8x for fp16 qa beam search example (#9752) * Pad to 8x for fp16 qa example (#9752) * Pad to 8x for fp16 seq2seq example (#9752) * Pad to 8x for fp16 glue example (#9752) * Pad to 8x for fp16 new ner example (#9752) * update script template #9752 * Update examples/multiple-choice/run_swag.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update examples/question-answering/run_qa.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update examples/question-answering/run_qa_beam_search.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * improve code quality #9752 Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> |
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| .. | ||
| {{cookiecutter.directory_name}} | ||
| cookiecutter.json | ||
| README.md | ||
How to add a new example script in 🤗 Transformers
This folder provide a template for adding a new example script implementing a training or inference task with the models in the 🤗 Transformers library. To use it, you will need to install cookiecutter:
pip install cookiecutter
or refer to the installation page of the cookiecutter documentation.
You can then run the following command inside the examples folder of the transformers repo:
cookiecutter ../templates/adding_a_new_example_script/
and answer the questions asked, which will generate a new folder where you will find a pre-filled template for your example following the best practices we recommend for them.
Adjust the way the data is preprocessed, the model is loaded or the Trainer is instantiated then when you're happy, add
a README.md in the folder (or complete the existing one if you added a script to an existing folder) telling a user
how to run your script.
Make a PR to the 🤗 Transformers repo. Don't forget to tweet about your new example with a carbon screenshot of how to run it and tag @huggingface!