image, predicts the added noise, and removes the predicted noise from the initial latent image to get the new latent image. Lastly, a decoder decodes the new latent image back into an image. With 🤗 Diffusers, this is as easy as 1-2-3: Load a checkpoint into the AutoPipelineForImage2Image class; this pipeline automatically handles loading the correct pipeline class  based on the checkpoint:   Copied import torch
from diffusers import AutoPipelin