load_model

app.py

@@ -19,6 +19,8 @@ def load_model():
       controlnet=ControlNetModel.from_pretrained("yeq6x/Image2PositionColor_v3"),
   ).to("cuda")
   pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
+  
+load_model()
 
 def convert_pil_to_opencv(pil_image):
   return np.array(pil_image)
@@ -134,9 +136,6 @@ def outpaint_image(image):
 
 @spaces.GPU
 def predict_image(cond_image, prompt, negative_prompt):
-  if pipe is None:
-    load_model()
-
   generator = torch.Generator()
   generator.manual_seed(random.randint(0, 2147483647))