Upload app.py

app.py

@@ -13,6 +13,11 @@ PATH = "wine_model.pth"
 
 model.load_state_dict(torch.load(PATH, weights_only=False))
 
+def forward(model, input):
+  preds = model(input)
+  predicted_class = torch.argmax(preds, dim=-1) + 4
+  return predicted_class
+
 def process_data(input_dataframe):
     # Perform operations on the input_dataframe
     if isinstance(input_dataframe, pd.DataFrame):