Update app.py

app.py

@@ -62,11 +62,11 @@ salarybracket_ga = gr.Interface(fn=salarybracket,
                                 ],
                                 outputs="text",
                                 examples = [
-                                              [28,Private,Bachelors,13,Married-civ-spouse,Prof-specialty,Wife,Black,Female,0,0,40,Cuba],
-                                              [38,Private,Some-college,10,Divorced,Craft-repair,Own-child,White,Male,0,0,58,Poland],
-                                              [44,Private,Some-college,10,Married-civ-spouse,Transport-moving,Husband,White,Male,0,0,40,United-States],
-                                              [29,Private,HS-grad,9,Never-married,Machine-op-inspct,Own-child,Asian-Pac-Islander,Male,0,0,40,Germany],
-                                              [31,Private,HS-grad,9,Separated,Machine-op-inspct,Unmarried,White,Female,0,2238,40,United-States],
+                                            [27,Private,Assoc-voc,11,Never-married,Other-service,Not-in-family,Asian-Pac-Islander,Female,0,0,40,Philippines],
+                                            [31,Private,10th,6,Married-civ-spouse,Machine-op-inspct,Husband,White,Male,0,0,40,United-States],
+                                            [34,Self-emp-inc,Masters,14,Never-married,Exec-managerial,Not-in-family,White,Female,4787,0,45,France],
+                                            [47,Local-gov,Masters,14,Married-civ-spouse,Prof-specialty,Husband,White,Male,0,0,40,United-States],
+                                            [43,Private,Masters,14,Never-married,Exec-managerial,Not-in-family,White,Female,0,0,45,United-States],
                                            ],   
                                 title="Salary Bracket Prediction",
                                 description="Predicting Income Bracket Using TensorFlow",