...     image_pil = PIL.Image.fromarray(image_processed[0])
...     display(f"Image at step {i}")
...     display(image_pil)
```  
To speed up the denoising process, move the input and model to a GPU:  
```py
>>> model.to("cuda")
>>> noisy_sample = noisy_sample.to("cuda")
```  
Now create a denoising loop that predicts the residual of the less noisy sample, and computes the less noisy sample with the scheduler:  
```py
>>> import tqdm

>>> sample = noisy_sample