Update app.py

app.py

@@ -15,10 +15,10 @@ ckpt = "sdxl_lightning_4step_unet.safetensors" # Use the correct ckpt for your s
 pipe_box=[]
 @spaces.GPU
 def init():
-    device="cuda"
-    unet = UNet2DConditionModel.from_config(base, subfolder="unet").to("cuda", torch.float16)
-    unet.load_state_dict(load_file(hf_hub_download(repo, ckpt), device="cuda"))
-    pipe = StableDiffusionXLPipeline.from_pretrained(base, unet=unet, torch_dtype=torch.float16, variant="fp16").to("cuda")
+    device="cuda:0"
+    unet = UNet2DConditionModel.from_config(base, subfolder="unet").to(device, torch.float16)
+    unet.load_state_dict(load_file(hf_hub_download(repo, ckpt), device=device))
+    pipe = StableDiffusionXLPipeline.from_pretrained(base, unet=unet, torch_dtype=torch.float16, variant="fp16").to(device)
     # Ensure sampler uses "trailing" timesteps.
     pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing")
     pipe_box.append(pipe)