y import Audio
from diffusers import DiffusionPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"
pipe = DiffusionPipeline.from_pretrained("teticio/audio-diffusion-256").to(device)

output = pipe()
display(output.images[0])
display(Audio(output.audios[0], rate=mel.get_sample_rate()))  For latent audio diffusion:   Copied import torch
from IPython.display import Audio
from diffusers import DiffusionPipeline

device = "cuda" if torc