StableDiffusionPipeline {
"_class_name": "StableDiffusionPipeline",
"_diffusers_version": "0.21.4",
...,
"scheduler": [
"diffusers",
"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:  
```python
>>> pipeline.to("cuda")
```