Upload folder using huggingface_hub

app.py

@@ -7,7 +7,13 @@ from flask import Flask, request, jsonify
 super_kart_api = Flask("Super Kart Price Predictor")
 
 # Load the trained machine learning model
-model = joblib.load("backend_files/super_kart_model_v1_0.joblib")
+model_path = "super_kart_model_v1_0.joblib"
+
+try:
+    model = joblib.load(model_path)
+    print(f"Model loaded successfully from {model_path}")
+except FileNotFoundError:
+    raise FileNotFoundError(f"Model file not found at {model_path}. Ensure it's uploaded to the repo root.")
 
 # Expected feature names from the model (adjust if your training columns differ)
 EXPECTED_COLUMNS = [