Superhero Diffusion

Introduction

Superhero-Diffusion is a text-to-image model designed to generate images in the style of comic art. It was trained using the works of Pepe Larraz, although he is not affiliated with this project. The model generates images using the comicmay artsyle token.

Architecture

The model is structured to convert textual descriptions into comic-style images. It leverages advanced diffusion techniques for high-quality visual outputs, focusing on detailed and stylistically consistent artwork.

Training

Superhero-Diffusion was trained using a dataset inspired by comic art. The training process involved refining the model to capture the unique elements of comic illustrations, allowing it to produce images that reflect this specific artistic style.

Guide: Running Locally

1. Installation: Clone the repository from Hugging Face and install the necessary dependencies. Ensure you have Python and pip installed.
2. Setup: Configure the environment and download the pre-trained model weights.
3. Execution: Use the provided scripts to input text prompts and generate images.
4. Hardware Recommendation: For optimal performance, especially when generating high-resolution images, consider using a cloud GPU service, such as Google Cloud, AWS, or Azure.

License

The Superhero-Diffusion model is licensed under the CreativeML OpenRAIL-M license, which governs its use and distribution.