>>> model = UNet2DModel.from_pretrained("google/ddpm-cat-256", use_safetensors=True).to("cuda") Set the number of timesteps to run the denoising process for:   Copied >>> scheduler.set_timesteps(50) Setting the scheduler timesteps creates a tensor with evenly spaced elements in it, 50 in this example. Each element corresponds to a timestep at which the model denoises an image. When you create the denoising loop later, you’ll iterate over this tensor to denoise an image:   Copied >>> scheduler.timesteps