Next, generate some initial random noise as a starting point for the diffusion process. This is the latent representation of the image, and it'll be gradually denoised. At this point, the `latent` image is smaller than the final image size but that's okay though because the model will transform it into the final 512x512 image dimensions later.  
<Tip>  
💡 The height and width are divided by 8 because the `vae` model has 3 down-sampling layers. You can check by running the following:  
```py