Attention Distillation: A Unified Approach to Visual Characteristics Transfer
Project Page
π₯π₯ News
2025/03/08: We provide a new notebook with
Style-specific T2I Generation with Flux.1-dev. See Issue 1 for more details.2025/03/05: We add
tilingto enable seamless textures generation. See Issue 3 for more details.2025/03/01: We provide a simple HuggingFaceπ€ demo. Check it out here !
Setup
This code was tested with Python 3.10, Pytorch 2.5 and Diffusers 0.32.
Examples
Texture Synthesis
- See [Texture Synthesis] part of ad notebook for generating texture images using SD1.5.
Style/Appearance Transfer
- See [Style/Appearance Transfer] part of ad notebook for style/appearance transfer using SD1.5.
Style-specific T2I Generation
- See [Style-specific T2I Generation] part of ad notebook for style-specific T2I generation using SD1.5 or SDXL.
VAE Finetuning
python train_vae.py \
--image_path=/path/to/image \
--vae_model_path=/path/to/vae
Web UI
Run the following command to start the Web UI:
python app.py
The Web UI will be available at http://localhost:7860.
ComfyUI
We also provide an implementation of Attention Distillation for ComfyUI. For more details, see here.
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
π
Ask for provider support



