README change

app.py

@@ -2,11 +2,8 @@
 import streamlit as st
 import joblib
 import pandas as pd
-
 from sklearn.linear_model import LinearRegression
 
-
-# Loading the model
 pipe = joblib.load('lr_regression_ny2019.pkl')
 
 st.title('Airbnb price predictor')
@@ -73,11 +70,4 @@ if submit_button:
 
     # Display the prediction
     st.header("Predicted Airbnb price")
-    st.write(f"the prediction is {prediction_value:.2f} dollar!")
-    
-st.markdown(
-    """
-    See how this model was created on Kaggle:<br>
-    [🍷 Wine Quality - EDA, Prediction and Deploy](https://www.kaggle.com/code/lusfernandotorres/wine-quality-eda-prediction-and-deploy/notebook)
-    """, unsafe_allow_html=True
-)
+    st.write(f"the prediction is {prediction_value:.2f} dollar!")