flush()
```  
Finally, decode the latents with the VAE into an image. The VAE is typically small enough to be loaded on a single GPU.  
```py
from diffusers import AutoencoderKL
from diffusers.image_processor import VaeImageProcessor
import torch

vae = AutoencoderKL.from_pretrained(ckpt_id, subfolder="vae", torch_dtype=torch.bfloat16).to("cuda")
vae_scale_factor = 2 ** (len(vae.config.block_out_channels))
image_processor = VaeImageProcessor(vae_scale_factor=vae_scale_factor)