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History

Albert Villanova del Moral a14b055b65 Pass datasets trust_remote_code (#31406 ) * Pass datasets trust_remote_code * Pass trust_remote_code in more tests * Add trust_remote_dataset_code arg to some tests * Revert "Temporarily pin datasets upper version to fix CI" This reverts commit `b7672826ca`. * Pass trust_remote_code in librispeech_asr_dummy docstrings * Revert "Pin datasets<2.20.0 for examples" This reverts commit `833fc17a3e`. * Pass trust_remote_code to all examples * Revert "Add trust_remote_dataset_code arg to some tests" to research_projects * Pass trust_remote_code to tests * Pass trust_remote_code to docstrings * Fix flax examples tests requirements * Pass trust_remote_dataset_code arg to tests * Replace trust_remote_dataset_code with trust_remote_code in one example * Fix duplicate trust_remote_code * Replace args.trust_remote_dataset_code with args.trust_remote_code * Replace trust_remote_dataset_code with trust_remote_code in parser * Replace trust_remote_dataset_code with trust_remote_code in dataclasses * Replace trust_remote_dataset_code with trust_remote_code arg		2024-06-17 17:29:13 +01:00
..
{{cookiecutter.directory_name}}	Pass datasets trust_remote_code (#31406 )	2024-06-17 17:29:13 +01:00
cookiecutter.json	Update the example template for a no Trainer option (#10865 )	2021-03-23 10:02:39 -04:00
README.md	[Docs] Add language identifiers to fenced code blocks (#28955 )	2024-02-12 10:48:31 -08:00

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!