Summary

This chapter covers the newest and best Stable Diffusion model – SDXL. We first introduced the basics of SDXL and why it is powerful and efficient, and then we drilled down into each component of the newly released model, covering VAE, UNet, text encoders, and the new two-stage design.

We provided a sample code for each of the components to help you understand SDXL inside out. These code samples can also be used to leverage the power of the individual components. For example, we can use VAE to compress images and a text encoder to generate text embeddings for images.

In the second half of this chapter, we covered some common use cases of SDXL, such as loading community-shared checkpoint models, using the image-to-image pipeline to enhance and upscale images, and introducing a simple and effective solution to load multiple LoRA models into one pipeline. Finally, we provided an end-to-end solution to use unlimited length-weighted prompts for SDXL.

With the help...