Update app.py

app.py

@@ -9,11 +9,12 @@ pipe = StableDiffusionPipeline.from_pretrained(
 ).to(device)
 
 def generate(prompt, steps, guidance, seed):
-    generator = torch.Generator(device).manual_seed(int(seed)) if seed else None
-    img = pipe(prompt, num_inference_steps=int(steps),
-               guidance_scale=float(guidance),
-               generator=generator).images[0]
-    return img
+    gen = None if seed == 0 else torch.manual_seed(seed)
+    image = pipe(prompt,
+                 num_inference_steps=int(steps),
+                 guidance_scale=float(guidance),
+                 generator=gen).images[0]
+    return image
 
 with gr.Blocks() as demo:
     gr.Markdown("# Stable Diffusion Text→Image Generation Demo")