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ddpm-ema-celebahq-256

Unconditional Image Generation Diffusers PyTorch DDPMPipeline
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@@ -39,7 +39,7 @@ model_id = "google/ddpm-ema-celebahq-256"
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  ddpm = DDPMPipeline.from_pretrained(model_id) # you can replace DDPMPipeline with DDIMPipeline or PNDMPipeline for faster inference
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  # run pipeline in inference (sample random noise and denoise)
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- image = ddpm().image
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  # save image
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  ddpm = DDPMPipeline.from_pretrained(model_id) # you can replace DDPMPipeline with DDIMPipeline or PNDMPipeline for faster inference
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  # run pipeline in inference (sample random noise and denoise)
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+ image = ddpm().images[0]
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  # save image