pipeline.enable_xformers_memory_efficient_attention() You’ll notice throughout the guide, we use enable_model_cpu_offload() and enable_xformers_memory_efficient_attention(), to save memory and increase inference speed. If you’re using PyTorch 2.0, then you don’t need to call enable_xformers_memory_efficient_attention() on your pipeline because it’ll already be using PyTorch 2.0’s native scaled-dot product attention. Load an image to pass to the pipeline:   Copied init_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") Pass a prompt and image to the pipeline to generate an image:   Copied prompt = "cat wizard, gandalf, lord of the rings, detailed, fantasy, cute, adorable, Pixar, Disney, 8k"