Update app

app.py

@@ -15,10 +15,10 @@ model_dir = model.download()
 model = joblib.load(model_dir + "/wine_model.pkl")
 print("Model downloaded")
 
-def wine(_type,fixed_acidity,volatile_acidity,citric_acid,residual_sugar,chlorides,free_sulfur_dioxide,total_sulfur_dioxide,density,ph,sulphates,alcohol,quality):
+def wine(type,fixed_acidity,volatile_acidity,citric_acid,residual_sugar,chlorides,free_sulfur_dioxide,total_sulfur_dioxide,density,ph,sulphates,alcohol,quality):
     print("Calling function")
-    df = pd.DataFrame([[_type,fixed_acidity,volatile_acidity,citric_acid,residual_sugar,chlorides,free_sulfur_dioxide,total_sulfur_dioxide,density,ph,sulphates,alcohol,quality]], 
-                      columns=['_type','fixed_acidity','volatile_acidity','citric_acid','residual_sugar','chlorides','free_sulfur_dioxide','total_sulfur_dioxide','density','ph','sulphates','alcohol','quality'])
+    df = pd.DataFrame([[type,fixed_acidity,volatile_acidity,citric_acid,residual_sugar,chlorides,free_sulfur_dioxide,total_sulfur_dioxide,density,ph,sulphates,alcohol,quality]], 
+                      columns=['type','fixed_acidity','volatile_acidity','citric_acid','residual_sugar','chlorides','free_sulfur_dioxide','total_sulfur_dioxide','density','ph','sulphates','alcohol','quality'])
     print("Predicting")
     print(df)
     # 'res' is a list of predictions returned as the label.
@@ -37,7 +37,7 @@ demo = gr.Interface(
     description="Experiment with wine features to predict which quality of wine it is.",
     allow_flagging="never",
     inputs=[
-        gr.Number(value=0, label="_type 0 for white, 1 for red"),
+        gr.Number(value=0, label="type 0 for white, 1 for red"),
         gr.Number(value=7.0, label="fixed_acidity"),
         gr.Number(value=0.0, label="volatile_acidity"),
         gr.Number(value=0.0, label="citric_acid"),