What is a stable diffusion model?

As diffusion models allow us to condition image generation with prompts, we can generate images of our choice. Among these text-conditioned diffusion models, Stable Diffusion is the most famous because of its open-source nature. In this article, we will break down the Stable Diffusion model into the individual components that make it up.

What is the difference between stable diffusion and Mo Di diffusion?

These images are much more artistic and dynamic compared to the base Stable Diffusion model. The Openjourney model has been trained on image outputs from Midjourney. The Mo Di Diffusion model adds Disney art style to any image that we create. Figure 16. Mo Di Diffusion.

What is the training process for stable diffusion?

The training process for Stable Diffusion offers a plethora of options, each with their own advantages and disadvantages. Essentially, most training methods can be utilized to train a singular concept such as a subject or a style, multiple concepts simultaneously, or based on captions (where each training picture is trained for multiple tokens ).

How does stable diffusion work?

Stable Diffusion works on the latent space of images rather than on the pixel space of images. Other generative diffusion models like DALL-E 2 and Imagen work on the pixel space of images. This makes them slower and, in the process, consumes more memory.