This repository provides Stable Diffusion Web UI notebooks for running through Google Colab.
Lora
This repository demonstrates low rank adaptation for quickly fine tuning diffusion models.

About Lora
Lora is an open source repository that implements low-rank adaptation (LoRA) for fine-tuning text-to-image diffusion models, particularly Stable Diffusion. Instead of retraining the entire model, it trains a small set of added weights, which the project describes as much faster than the DreamBooth method and as producing files of about 1 MB to 6 MB.
The repository includes training scripts, example LoRA models, and tools for merging LoRA files together. Its LoRA format has been integrated into the diffusers library, but the README notes that the diffusers version uses a different file format. The project also states that LoRA sometimes performs better than full fine-tuning, but it describes extensive comparisons as future work.
Key features
- Low-rank adaptation fine-tuning of Stable Diffusion models, described as faster than DreamBooth
- Trained LoRA files of about 1 MB to 6 MB that are easy to share
- Compatibility with the Hugging Face diffusers library
- Inpainting training support using an inpainting base model
- Merging of LoRA files and checkpoints into combined models
- Pipeline for fine-tuning CLIP, U-Net, and token together
- Produces small fine-tuned files that are easy to share and download
- Integrated into the diffusers library and supports inpainting
- The claim that LoRA sometimes outperforms full fine-tuning has not been extensively compared
- The diffusers-integrated version uses a different file format from this repository
Lora at a glance
- Website
- github.com/cloneofsimo/lora
- Category
- AI & Machine Learning › AI Image Generators
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Lora FAQ
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