iffusers",
    "PNDMScheduler"
  ],
  ...,
  "unet": [
    "diffusers",
    "UNet2DConditionModel"
  ],
  "vae": [
    "diffusers",
    "AutoencoderKL"
  ]
}
We strongly recommend running the pipeline on a GPU because the model consists of roughly 1.4 billion parameters.
You can move the generator object to a GPU, just like you would in PyTorch:


	Copied
>>> pipeline.to("cuda")
Now you can pass a text prompt to the pipeline to generate an imag