_pretrained("google/ddpm-ema-celebahq-256", scheduler=scheduler)
>>> pipe = pipe.to("cuda")

>>> generator = torch.Generator(device="cuda").manual_seed(0)
>>> output = pipe(
...     image=original_image,
...     mask_image=mask_image,
...     num_inference_steps=250,
...     eta=0.0,
...     jump_length=10,
...     jump_n_sample=10,
...     generator=generator,
... )
>>> inpainted_image = output.images[0]  ImagePipelineOutput  class diffusers.I