The goal of this article is to get you up to speed on stable diffusion. You will learn the main use cases, how stable diffusion works, debugging options, how to use it to your advantage and how to extend it. I) Main use cases of stable diffusion There are a lot of options of how to use stable diffusion, but here are the four main use cases: Overview of the four main uses cases for stable diffusion.
Stable diffusion is all the rage in the deep learning community at the moment. It’s trending on Twitter at #stablediffusion and gaining large amounts of attention all over the internet. We’ll take a look into the reasons for all the attention to stable diffusion and more importantly see how it works under the hood by considering the well-written paper “High-resolution image synthesis with latent diffusion models” by Rombach et al which is the foundation of the system.