make_image_grid([init_image, mask_image, image], rows=1, cols=3)   Refine image quality SDXL includes a refiner model specialized in denoising low-noise stage images to generate higher-quality images from the base model. There are two ways to use the refiner: use the base and refiner models together to produce a refined image use the base model to produce an image, and subsequently use the refiner model to add more details to the image (this is how SDXL was originally trained)  Base + refiner model When you use the base and refiner model together to generate an image, this is known as an ensemble of expert denoisers. The ensemble of expert denoisers approach requires fewer overall denoising steps versus passing the base model’s output to the refiner model, so it should be significantly faster to run. However, you won’t be able to inspect the base model’s output because it still contains a large amount of noise. As an ensemble of expert denoisers, the base model serves as the expert during the high-noise diffusion stage and the refiner model serves as the expert during the low-noise diffusion stage. Load the base and refiner model:   Copied from diffusers import DiffusionPipeline