Update app.py

app.py

@@ -75,7 +75,7 @@ def predict_churn(
     df[cat_cols] = df[cat_cols].astype("object")
     
     # Passing data to pipeline to make prediction
-    output = pipeline_of_my_app.predict_proba(df)
+    output = pipeline_of_my_app.predict(df)
     
     # Labelling Model output
     if output == 0:
@@ -120,4 +120,4 @@ with gr.Blocks() as demo:
     make_prediction.click(predict_churn, inputs, output_prediction)
 
 # Launching app
-demo.launch(debug=True)
+demo.launch(debug=True,inline=False,)