Stable Diffusion with 🧨 Diffusers
Open In Colab
Stable Diffusion 🎨 ...using 🧨 Diffusers

Stable Diffusion is a text-to-image latent diffusion model created by the researchers and engineers from CompVis, Stability AI and LAION. It is trained on 512x512 images from a subset of the LAION-5B database. LAION-5B is the largest, freely accessible multi-modal dataset that currently exists.

In this post, we want to show how to use Stable Diffusion with the 🧨 Diffusers library, explain how the model works and finally dive a bit deeper into how diffusers allows one to customize the image generation pipeline.

Note: It is highly recommended to have a basic understanding of how diffusion models work. If diffusion models are completely new to you, we recommend reading one of the following blog posts:

The Annotated Diffusion Model
Getting started with 🧨 Diffusers
Now, let's get started by generating some images 🎨.#Stable Diffusion

Stable Diffusion in JAX / Flax !
Open In Colab
🤗 Hugging Face Diffusers supports Flax since version 0.5.1! This allows for super fast inference on Google TPUs, such as those available in Colab, Kaggle or Google Cloud Platform.

This post shows how to run inference using JAX / Flax. If you want more details about how Stable Diffusion works or want to run it in GPU, please refer to this Colab notebook.

If you want to follow along, click the button above to open this post as a Colab notebook.

First, make sure you are using a TPU backend. If you are running this notebook in Colab, select Runtime in the menu above, then select the option "Change runtime type" and then select TPU under the Hardware accelerator setting.

Note that JAX is not exclusive to TPUs, but it shines on that hardware because each TPU server has 8 TPU accelerators working in parallel.#Stable Diffusion