pository’s directory:


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from diffusers import UNet2DModel

repo_id = "google/ddpm-cifar10-32"
model = UNet2DModel.from_pretrained(repo_id)
You can also load and save model variants by specifying the variant argument in ModelMixin.from_pretrained() and ModelMixin.save_pretrained():


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from diffusers import UNet2DConditionModel

model = UNet2DConditionModel.from_pretrained("runwayml/stable-diffusion-v1-5", subfolder="unet", variant