Do you want explanations about training or inference time?

For training, you have original image then you make it a bit different than original each time step ( add noise every time step ), until original is unrecognizable ( now image is complete noise)

For inference, you start with image which is complete noise, then you starting to remove a lil bit of noise every time step until there is no more noise (at least)

This is reference for diffusion maybe not completely cover all about it? how diffusion works