Update app.py

app.py

@@ -49,12 +49,10 @@ image_examples = [
     ]
     
 ]
-class PipelineContainer:
-    pipe = None
+
 @spaces.GPU(duration=120)
 def load_model(base_model_path, lora_path):
-    global pipe
-    PipelineContainer.pipe = pipe 
+    global pipe 
     transformer = FluxTransformer2DModel.from_pretrained(base_model_path, subfolder='transformer', torch_dtype=torch.bfloat16)
     gr.Info(str(f"Model loading: {int((40 / 100) * 100)}%"))
     # enable image inputs
@@ -105,7 +103,6 @@ def predict(
     mask_paths
 
 ):
-    pipe = PipelineContainer.pipe
     global image_path, mask_path
     gr.Info(str(f"Set seed = {seed}"))
     if image_paths is not None:
@@ -150,6 +147,7 @@ def predict(
         gray_image_pil = Image.fromarray(gray_image).convert('L')
     else:
         gray_image_pil = input_image["layers"][0]
+    load_model(base_model_path=base_model_path, lora_path=lora_path)
     result = pipe(
         prompt=prompt,
         control_image=input_image["background"].convert("RGB"),