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lora

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Jupyter Notebook

Project Description

Using Low-rank adaptation to quickly fine-tune diffusion models.

lora: Using Low-rank adaptation to quickly fine-tune diffusion models.

Project Title

lora — Fast Fine-Tuning of Diffusion Models with Low-Rank Adaptation

Overview

lora is an open-source project that enables quick fine-tuning of diffusion models using Low-rank Adaptation (LoRA). This method allows for faster fine-tuning compared to traditional methods, resulting in smaller model sizes that are easier to share and download. The project is compatible with diffusers and supports inpainting, making it a versatile tool for AI developers working with text-to-image diffusion models.

Key Features

  • Fast fine-tuning of Stable Diffusion models using Low-rank Adaptation
  • Small end results (1MB to 6MB) for easy sharing and downloading
  • Compatibility with diffusers library
  • Support for inpainting
  • Merge checkpoints and build recipes by merging LoRAs together
  • Pipeline to fine-tune CLIP, Unet, and token for better results
  • Out-of-the-box multi-vector pivotal tuning inversion

Use Cases

  • AI developers looking to fine-tune diffusion models quickly and efficiently
  • Researchers needing small, easily shareable models for text-to-image tasks
  • Content creators who want to customize their AI-generated images with minimal resources

Advantages

  • Significantly faster fine-tuning compared to traditional methods
  • Smaller model sizes for easier distribution and deployment
  • Improved performance in some cases compared to full fine-tuning
  • Integration with Huggingface Spaces for easy web demo access

Limitations / Considerations

  • The project is relatively new, and extensive comparisons with full fine-tuning are still needed
  • The effectiveness of LoRA may vary depending on the specific use case and dataset
  • The project's license is currently unknown, which may affect its use in commercial applications

Similar / Related Projects

  • DreamBooth: A method for personalizing text-to-image models, which lora can potentially enhance with faster fine-tuning.
  • Stable Diffusion: A popular text-to-image diffusion model that can be fine-tuned using lora for faster results.
  • CLIP: A model that can be combined with lora for improved text-to-image generation tasks.

Basic Information

  • GitHub: lora
  • Stars: 7,471
  • License: Unknown
  • Last Commit: 2025-11-13

📊 Project Information

  • Project Name: lora
  • GitHub URL: https://github.com/cloneofsimo/lora
  • Programming Language: Jupyter Notebook
  • ⭐ Stars: 7,471
  • 🍴 Forks: 495
  • 📅 Created: 2022-12-08
  • 🔄 Last Updated: 2025-11-13

🏷️ Project Topics

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Project Information

Created on 12/8/2022
Updated on 12/30/2025