Update app.py

app.py

@@ -123,7 +123,7 @@ effnetb2_model  , effnet_b2_transforms = create_effnetb2_model(num_classes = 101
 # Load save weights
 effnetb2_model.load_state_dict(
   torch.load(
-    f='11_pretrained_effnet_feature_extractor_food101.pth',
+    f='11_pretrained_effnet_feature_extractor_food101_fine_tune.pth',
     map_location = torch.device('cpu') # Load the model on CPU
   )
 )
@@ -149,7 +149,7 @@ def predict(img) -> Tuple[Dict,float] :
 ### 4. Gradio app - our Gradio interface + launch command
 
 title = 'FoodVision Big'
-description = 'An EfficientNetB2 Feature extractor computer vision model to classifiy 101 Food images '
+description = 'An FineTune last 4 Sequential layers of EfficientNetB2 model to classifiy 101 Food images '
 article = 'created at PyTorch Model Deployment'
 
 # Create example list