Update app.py

app.py

@@ -14,7 +14,7 @@ ckpt = "sdxl_lightning_4step_unet.safetensors" # Use the correct ckpt for your s
 # Load model.
 pipe_box=[]
 @spaces.GPU
-def inti():
+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"))
@@ -22,6 +22,7 @@ def inti():
     # Ensure sampler uses "trailing" timesteps.
     pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing")
     pipe_box.append(pipe)
+init()
 def run():
     pipe=pipe_box[0]
     # Ensure using the same inference steps as the loaded model and CFG set to 0.