Update description

app.py

@@ -66,6 +66,14 @@ unique_sex = sorted(X_train["sex"].unique())
 unique_country = sorted(X_train["native.country"].unique())
 
 with gr.Blocks() as demo:
+    gr.Markdown("""
+    # Income Classification with XGBoost 💰
+    
+    This example shows how to load data from the hugging face hub to train an XGBoost classifier and
+    demo the predictions with gradio.
+
+    The source is [here](https://huggingface.co/spaces/gradio/xgboost-income-prediction-with-explainability).
+    """)
     with gr.Row():
         with gr.Column():
             age = gr.Slider(label="Age", minimum=17, maximum=90, step=1, randomize=True)