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app.py

@@ -4,12 +4,14 @@ import mlflow.sklearn
 import pandas as pd
 import numpy as np
 from sklearn.preprocessing import LabelEncoder
+import joblib
 
 # Load the trained model (assuming it's saved in MLflow)
-logged_model = '/'
+logged_model = 'model.pkl'
+model = joblib.load(logged_model)
 
 # Load model
-model = mlflow.sklearn.load_model(logged_model)
+# model = mlflow.sklearn.load_model(logged_model)
 
 # Define categorical features and their distinct values
 categorical_features = ['employment_type', 'job_category', 'experience_level',