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CONTRIBUTING.md

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Contributing to llama-recipes

We want to make contributing to this project as easy and transparent as possible.

Pull Requests

We actively welcome your pull requests.

  1. Fork the repo and create your branch from main.
  2. If you've added code that should be tested, add tests.
  3. If you've changed APIs, update the documentation.
  4. Ensure the test suite passes.
  5. Make sure your code lints.
  6. If you haven't already, complete the Contributor License Agreement ("CLA").

Contributor License Agreement ("CLA")

In order to accept your pull request, we need you to submit a CLA. You only need to do this once to work on any of Facebook's open source projects.

Complete your CLA here: https://code.facebook.com/cla

Issues

We use GitHub issues to track public bugs. Please ensure your description is clear and has sufficient instructions to be able to reproduce the issue.

Facebook has a bounty program for the safe disclosure of security bugs. In those cases, please go through the process outlined on that page and do not file a public issue.

License

By contributing to llama-recipes, you agree that your contributions will be licensed under the LICENSE file in the root directory of this source tree.

Tests

Llama-recipes currently comes with a basic set of unit tests (covering the parts of the main training script and training loop) but we strive to increase our test coverage in the future in order to mitigate silent errors. When submitting a new feature PR please make sure to cover the newly added code with a unit test. Run the tests locally to ensure the new feature does not break an old one. We use pytest for our unit tests and to run them locally you need to install llama-recipes with optional [tests] dependencies enabled:

pip install --extra-index-url https://download.pytorch.org/whl/test/cu118 llama-recipes[tests]

For development and contributing to llama-recipes please install from source with all optional dependencies:

pip install -U pip setuptools
pip install --extra-index-url https://download.pytorch.org/whl/test/cu118 -e .[tests,auditnlg,vllm]

The unit tests can be found in the tests folder and you can run them from the main directory using:

python -m pytest tests/

To run all tests of a single file you can give the filename directly:

python -m pytest tests/test_finetuning.py

To run a specific test you can filter for its name with

python -m pytest tests/test_finetuning.py -k test_finetuning_peft

To add a new test simply create a new test file under the tests folder (filename has to start with test_). Group tests spanning the same feature in the same file and create a subfolder if the tests are very extensive.