e though, you’ll use DiffusionPipeline for unconditional image generation with DDPM:


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>>> from diffusers import DiffusionPipeline

>>> generator = DiffusionPipeline.from_pretrained("google/ddpm-celebahq-256")
The DiffusionPipeline downloads and caches all modeling, tokenization, and scheduling components.
Because the model consists of roughly 1.4 billion parameters, we strongly recommend running it on GPU.
You can move the generator ob