Upload folder using huggingface_hub

Dockerfile

@@ -13,4 +13,4 @@ RUN pip install --no-cache-dir --upgrade -r requirements.txt
 # - `-w 4`: Uses 4 worker processes for handling requests
 # - `-b 0.0.0.0:7860`: Binds the server to port 7860 on all network interfaces
 # - `app:app`: Runs the Flask app (assuming `app.py` contains the Flask instance named `app`)
-CMD ["gunicorn", "-w", "4", "-b", "0.0.0.0:7860", "app:rental_price_predictor_api"]
+CMD ["gunicorn", "-w", "4", "-b", "0.0.0.0:7860", "app:superkart_predictor_api"]

app.py

@@ -8,7 +8,7 @@ from flask import Flask, request, jsonify  # For creating the Flask API
 superkart_predictor_api = Flask("SuperKart sales Predictor")
 
 # Load the trained machine learning model
-model = joblib.load("Super_Kart_predication_v1_0.joblib")
+model = joblib.load("deployment_files/Super_Kart_predication_v1_0.joblib")
 
 # Define a route for the home page (GET request)
 @superkart_predictor_api.get('/')
@@ -17,7 +17,7 @@ def home():
     This function handles GET requests to the root URL ('/') of the API.
     It returns a simple welcome message.
     """
-    return "Welcome to the Airbnb Rental Price Prediction API!"
+    return "Welcome to the SuperKart slares Prediction API!"
 
 # Define an endpoint for single property prediction (POST request)
 @superkart_predictor_api.post('/v1/sales')