Deploying Stable Diffusion locally

Stable Diffusion is a powerful text-to-image model that can generate realistic and detailed images based on natural language descriptions. It was developed by Stability AI in collaboration with academic researchers and non-profit organizations. Stable Diffusion is based on a latent diffusion model, a kind of deep generative neural network that iteratively denoises random noise until it produces the desired image. Stable Diffusion is open-source and can run on most consumer hardware with a GPU.

If you want to deploy and use Stable Diffusion, you can follow these steps:

1. Clone the Stable Diffusion repository from GitHub: https://github.com/AUTOMATIC1111/stable-diffusion-webui
2. Install the required dependencies using pip: pip install -r requirements.txt
3. Download the pretrained models from Google Drive: https://drive.google.com/drive/folders/1-3ONnPYcX9fOsqmZKjtL0oy0vQwQowvW
4. Run the web interface using streamlit: streamlit run app.py
5. Enter your text prompt in the input box and click “Generate” to see the output image.
6. You can also adjust the model parameters, such as resolution, temperature, and number of diffusion steps, using the sliders on the sidebar.
7. Enjoy creating amazing images with Stable Diffusion!

Quick note, if you are running Windows and want Cuda support, use this command

pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

On Linux:

conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia

Verifying install with the following python code:

import torch
torch.cuda.is_available()