SDXL 1, Stable diffusion XL run with LOW VRAM and Upsdcale

preview_player
Показать описание
Join us in this experimental live YouTube session as we explore the functionalities of Stable Diffusion XL (SDXL 1). This video will cover the following aspects:

download link:

Introduction to SDXL 1: Get a comprehensive overview of SDXL 1 and its capabilities in the realm of artificial intelligence.

Operating SDXL 1 with Low VRAM: Learn how to optimally operate SDXL 1 when working with low VRAM. We will discuss different techniques to maximize its performance on systems with limited resources.

Exploring Upscaling Features: We'll delve into the upscaling capabilities of SDXL 1 and how it can enhance your AI projects.

Hands-On Experimentation: Together, we will experiment with SDXL 1 to get a first-hand experience of its functionalities and possibilities.

Q&A: Finally, we will have a Q&A session, where I will answer your queries related to SDXL 1.

Remember, this is a learning process, and the unpredictable nature of AI makes it even more fascinating. So, be a part of this exciting journey, let's experiment, learn and grow together.

#sdxl #sdxl1 #stablediffusion #comfyui #live
Рекомендации по теме
Комментарии
Автор

Thanks! this is great news for people with low VRAM!

RazielDark
Автор

in the sdxl paper ”SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis”, it says that the output of base and refiner both are 128x128 with out vae, and then use vae to get to 1024x1024,I am confused

dxj
Автор

Can I use the same workflow of SDXL 0. 9 with this new model?

LLCinema
Автор

The Refiner (Advanced) and Base (Advanced) nodes used in your demo... Which custom node package are they from ?

BYTEcann