Update app.py

app.py

@@ -1,12 +1,14 @@
 import torch
 from diffusers import DiffusionPipeline
 import gradio as gr
+import spaces
 
 # Load the pre-trained diffusion model
 pipe = DiffusionPipeline.from_pretrained('ptx0/terminus-xl-velocity-v2', torch_dtype=torch.bfloat16)
 pipe.to('cuda')
 
 # Define the image generation function with adjustable parameters and a progress bar
+@spaces.GPU
 def generate(prompt, guidance_scale, num_inference_steps, negative_prompt):
     with gr.Progress(steps=num_inference_steps) as progress:
         for i in range(num_inference_steps):