Update app.py

app.py

@@ -49,10 +49,12 @@ image_examples = [
     ]
     
 ]
-
+class PipelineContainer:
+    pipe = None
 @spaces.GPU(duration=120)
 def load_model(base_model_path, lora_path):
     global pipe
+    PipelineContainer.pipe = 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
@@ -103,6 +105,7 @@ 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: