CogVideoX-LoRAs is a centralized repository for all LoRA (Low-Rank Adaptation) models created for CogVideoX. This project addresses the need for a unified platform to collect, share, and contribute to various LoRA models, making it easier for users, developers, and researchers to enhance their video generation workflows.
If you are looking to create your own LoRAs for CogVideoX, head over to CogVideoX-Factory. A multi-tool repository created for the CogVideoX model family, including LoRA training using 24GB or less. Developed by a-r-r-o-w.
- Comprehensive Collection: A growing repository of all available LoRAs created for CogVideoX.
- Community Contributions: Open to contributions from the community, fostering collaboration in LoRA model development.
- Easy Access: Clear organization and categorization of LoRA models for easy discovery and usage.
- Up-to-Date Listings: Regularly updated with the latest LoRA models, ensuring this repository remains the go-to source for CogVideoX customizations.
For a detailed list of available LoRA models, please refer to the LORA_MODELS.md file in the repository.
Contributions are welcome! If you would like to contribute to this repository, please follow these steps:
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Fork the Repository: Click the "Fork" button at the top right of the repository page.
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Clone Your Fork to your local machine:
git clone https://github.com/your-username/cogvideox-loras.git- Navigate to the Repository Directory:
cd cogvideox-loras- Run the
add_new_lora.pyScript to add a new LoRA model (only HF-Link and description needed):
python add_new_lora.pyThis script will fetch model data from Hugging Face and append it to the LORA_MODELS.md file.
- Commit Your Changes:
git add LORA_MODELS.md
git commit -m "Added new LoRA to list"- Push to Your Fork:
git push origin main- Open a Pull Request detailing your changes.
This project is licensed under the MIT License. See the LICENSE file for more information.
For inquiries or feedback, please contact [[email protected]].