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| title: README | |
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| # Welcome to the Lots-of-LoRAs Collection! | |
| ## Introduction | |
| We are proud to host the world's largest open collection of LoRAs (Low-Rank Adaption). This initiative is part of a broader effort to advance research and development in the field of LoRA and PEFT (Parameter Efficient Fine-Tuning). | |
| ## Project Description | |
| Our collection currently includes over 500 LoRAs, making it the most extensive open repository of its kind. This project aims to support and drive forward research by providing a comprehensive dataset of LoRAs for analysis, experimentation, and application development. | |
| By making these resources available to the community, we hope to encourage collaboration and innovation, helping to push the boundaries of what's possible in PEFT. | |
| We also include the exact data that these LoRAs were trained on, with the corresponding training, validation, and test splits. | |
| Details can be found in the paper: https://www.arxiv.org/abs/2407.00066 | |
| ## How to Contribute | |
| We are always looking for new contributions and collaborators: | |
| - **Contribute Data**: If you have LoRAs that you would like to share, please feel free to submit it to our collection. | |
| ## Contact Us | |
| Interested in contributing or have questions? Reach out to us at [email](mailto:[email protected]). | |
| ## Thank You! | |
| We appreciate your interest in our project and hope you will join us in this exciting venture. | |