fixed model state path

app.py

@@ -16,7 +16,7 @@ effnetb2, effnetb2_transforms = create_effnetb2_model(num_classes=3)
 
 # Load saved weights
 
-effnetb2.load_state_dict(torch.load(f="foodvision_mini/pretrained_effnetb2_feature_extractor_pizza_steak_sushi_20_percent.pth",
+effnetb2.load_state_dict(torch.load(f="pretrained_effnetb2_feature_extractor_pizza_steak_sushi_20_percent.pth",
                                     map_location=torch.device("cpu")))
 
 ### 3. Predict function ###
@@ -60,4 +60,4 @@ demo = gr.Interface(fn=predict, # maps inputs to outputs
                     description=description,
                     article=article)
 # launch the demo
-demo.launch()
+demo.launch(debug=False)