disco diffusion style

Introduction

The Disco Diffusion Style on Stable Diffusion via DreamBooth project involves fine-tuning the Stable Diffusion model to incorporate the Disco Diffusion style. This is achieved through DreamBooth, allowing users to generate images by modifying the instance_prompt with the specific style.

Architecture

The model is based on the Stable Diffusion architecture and utilizes the DreamBooth technique to teach the model new styles or concepts. This approach allows for customizations and the incorporation of unique artistic styles into the image generation process.

Training

The model can be fine-tuned using a set of training images that exemplify the Disco Diffusion style. Users can also train their own styles by using the provided Colab notebook for DreamBooth training. The training involves uploading concept images and adjusting the model to understand and replicate the desired artistic style.

Guide: Running Locally

To run the model locally, follow these steps:

1. Set up your Environment: Ensure you have Python and all necessary packages installed. It's recommended to use a virtual environment.
2. Install Diffusers Library: Use pip to install the Hugging Face Diffusers library.

   pip install diffusers
   

3. Download the Model: Access the model files from the Hugging Face model hub.
4. Run Inference: Use the Colab notebook for inference to perform inference with your trained model.

For better performance, consider using cloud GPUs from services such as Google Colab, AWS, or Azure, which provide the necessary computational resources.

License

The project is licensed under the MIT License, allowing for open use and modification of the model and its components.