Update app.py

app.py

@@ -124,7 +124,7 @@ refiner = StableDiffusionXLImg2ImgPipeline.from_pretrained(
 refiner.watermark = NoWatermark()
 print("Finish Loading Model!")
 
-@spaces.GPU()
+@spaces.GPU(duration=120)
 def generate_image(prompt, 
                    n_prompt="", 
                    style: str = DEFAULT_STYLE_NAME,
@@ -140,7 +140,7 @@ def generate_image(prompt,
     image_list = []
     for i in range(img_num):
         seed = int(randomize_seed_fn(seeds, random_seed))
-        generator = torch.Generator().manual_seed(seed)
+        generator = torch.Generator(device="cuda").manual_seed(seed)
         positive_prompt, negative_prompt = apply_style(style, prompt, n_prompt)
         image = pipe(positive_prompt, num_inference_steps=steps, 
                 guidance_scale=scale, height=height,