-ar 2:3  --beta --upbeta",
]

generator = [torch.Generator("cuda").manual_seed(1) for _ in range(len(prompts))]
images = pipeline(prompt=prompts, generator=generator, num_inference_steps=25).images
make_image_grid(images, 2, 2)   Next steps In this tutorial, you learned how to optimize a DiffusionPipeline for computational and memory efficiency as well as improving the quality of generated outputs. If you’re interested in making your pipeline e