image Want to generate images of something else? Take a look at the training guide to learn how to train a model to generate your own images. The output image is a PIL.Image object that can be saved:   Copied image.save("generated_image.png") You can also try experimenting with the num_inference_steps parameter, which controls the number of denoising steps. More denoising steps typically produce higher quality images, but it’ll take longer to generate. Feel free to play around with this parameter to see how it affects the image quality.   Copied image = generator(num_inference_steps=100).images[0]