Update app.py

app.py

@@ -1,4 +1,5 @@
 from diffusers import DiffusionPipeline
+import spaces
 import torch
 import PIL.Image
 import gradio as gr
@@ -8,6 +9,7 @@ pipeline = DiffusionPipeline.from_pretrained("1aurent/ddpm-mnist")
 device = "cuda" if torch.cuda.is_available() else "cpu"
 pipeline = pipeline.to(device=device)
 
+@spaces.GPU
 def predict(steps, seed):
     generator = torch.manual_seed(seed)
     for i in range(1,steps):