WARP

Welcome to WARP. This is our little organization for multimodal generative models, focusing on the visual domain. We have been working with generative image models a lot and will soon work on video models as well. Our main team consists of:

• Pablo Pernias
• Dominic Rampas
• Marc Aubreville
• Mats L. Richter

A special thanks to the Huggingface Team for helping to bring our research to Diffusers! (Special thanks to Kashif, Patrick and Sayak!)

Feel free to join our Discord channel!

Models:

Paella

• A simple & straightforward text-conditional image generation model that works on quantized latents.
• More details can be found in the paper, the blog post and the YouTube video.
• Only accessible through GitHub.

Würstchen

• An efficient text-to-image model to train and use for inference. Achieves competetive performance to state-of-the-art methods, while needing only a fraction of the compute.
• More details can be found in the paper.
• Versions:
• v1: Only accessible through GitHub.
• v2: Accessible through GitHub and Diffusers