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app.py

@@ -58,7 +58,9 @@ class FeatureEngineer(BaseEstimator, TransformerMixin):
 app = Flask("SuperKart Sales Predictor")
 
 # Load the trained churn prediction model
-model = joblib.load("XGBoostRegressor_BEST_Pipeline.joblib")
+#model = joblib.load("XGBoostRegressor_BEST_Pipeline.joblib")
+# passing the custom classes FeatureEngineer in a dictionary to the 'mmap_mode' argument.
+model = joblib.load("XGBoostRegressor_BEST_Pipeline.joblib", mmap_mode={'FeatureEngineer': FeatureEngineer})
 
 # Define a route for the home page
 @app.get('/')