a basic unconditional image generation model with a checkpoint trained on cat images:


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>>> from diffusers import UNet2DModel

>>> repo_id = "google/ddpm-cat-256"
>>> model = UNet2DModel.from_pretrained(repo_id)
To access the model parameters, call model.config:


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>>> model.config
The model configuration is a 🧊 frozen 🧊 dictionary, which means those parameters can’t be changed after the model is created. This is intentional and 