x_t-1
...     sample = scheduler.step(residual, t, sample).prev_sample

...     # 3. optionally look at image
...     if (i + 1) % 50 == 0:
...         display_sample(sample, i + 1) Sit back and watch as a cat is generated from nothing but noise! 😻   Next steps Hopefully, you generated some cool images with 🧨 Diffusers in this quicktour! For your next steps, you can: Train or finetune a model to generate your own images in the training tutorial