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Contribution Guide

There may still be many incomplete aspects in this project.

We look forward to your contributions to the repository in the following areas. If you complete the work mentioned above and are willing to submit a PR and share it with the community, upon review, we will acknowledge your contribution on the project homepage.

Model Algorithms

  • Support for model quantization inference (Int4 quantization project)
  • Optimization of model fine-tuning data loading (replacing the existing decord tool)

Model Engineering

  • Model fine-tuning examples / Best prompt practices
  • Inference adaptation on different devices (e.g., MLX framework)
  • Any tools related to the model
  • Any minimal fully open-source project using the CogVideoX open-source model

Code Standards

Good code style is an art. We have prepared a pyproject.toml configuration file for the project to standardize code style. You can organize the code according to the following specifications:

  1. Install the ruff tool
pip install ruff

Then, run the ruff tool

ruff check tools sat inference

Check the code style. If there are issues, you can automatically fix them using the ruff format command.

ruff format tools sat inference

Once your code meets the standard, there should be no errors.

Naming Conventions

  1. Please use English names, do not use Pinyin or other language names. All comments should be in English.
  2. Please strictly follow the PEP8 specification and use underscores to separate words. Do not use names like a, b, c.