Visualize every attention layer in the UNet for each word in the prompt.
attention.visualization.mov
Supported models
- Flux Dev
- Stable Diffusion 2.1
Make sure you have the following prerequisites installed on your system:
- python version 3.10
- nodejs
The following steps will include commands you can run in your terminal. The commands are written for UNIX based systems like MacOS and Linux.
For Flux Dev
Download the Flux Dev repository into the /models folder. You can download the repository from Huggingface here. You should have the following files in the /models folder:
- /models/black-forest-labs/FLUX.1-dev/flux1-dev.safetensors
- /models/black-forest-labs/FLUX.1-dev/ae.safetensors
You also need to download OpenAI's CLIP and Google's T5 encoders to the models repository. You should have the following files in the /models folder:
- /models/openai/clip-vit-large-patch14/model.safetensors
- /models/google/t5-v1_1-xxl/pytorch_model.bin
For Stable Diffusion 2.1
Download the Stable Diffusion 2.1 model into the /models folder. You can download the model from Huggingface here. After you have downloaded the model, the path to the model should be /models/v2-1_512-ema-pruned.safetensors
Next set up the Python server. In the root of the repository:
- Create a virtual env (optional)
python -m venv venv source venv/bin/activate
- Install requirements.txt
pip install -r requirements.txt
Now you can run the Python server with Uvicorn
uvicorn server:app --host 0.0.0.0 --port 8000
To set up the frontend, we will need to enter the web
directory and install packages with npm
cd web
npm install
Now we are ready to run the app
Boot up the Python server if you haven't already with:
uvicorn server:app --host 0.0.0.0 --port 8000
In another terminal, enter the frontend and run the start up script like so:
cd web
npm run dev
Now you are ready to use the app!