Update app.py

app.py

@@ -2,7 +2,7 @@ import pickle
 import gradio as gr
 
 # Load the pickled model
-with open('./xgb_waze.pickle , 'rb') as file:
+with open('./xgb_waze.pickle' , 'rb') as file:
     model = pickle.load(file)
 
 # Define the function for making predictions
@@ -45,11 +45,12 @@ salifort_ga = gr.Interface(fn=salifort,
                                         ],
                                outputs  = "text", title="Data-driven suggestions for Waze - User Churn", 
                                examples = [
-                                        [0, 3, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
-                                        [0, 3, 3, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1],
-                                        [0, 2, 3, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0],
-                                        [0, 6, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1]
-                                         ],
+                                            [30, 30, 207, 2239, 11, 12, 3919, 2182, 26, 25, 157, 0, 0, 0, 108, 131, 0, 0],
+                                            [47, 40, 144, 36, 353, 0, 10764, 4617, 18, 17, 633, 0, 0, 4, 140, 269, 2, 0],
+                                            [75, 61, 87, 2825, 67, 94, 243, 183, 2, 0, 0, 1, 0, 0, 80, 4, 2, 0, 0, 0],
+                                            [0, 0, 291, 1589, 447, 110, 1574, 1163, 17, 16, 98, 0, 0, 0, 81, 0, 2, 1, 0],
+                                            [56, 45, 82, 701, 80, 32, 1515, 691, 20, 15, 101, 1, 0, 0, 132, 34, 1, 0, 0]
+                                        ],
                                description="User Churn Prediction Using Machine Learning",
                                theme='dark'
                                )