| # ========================================================== | |
| # Example usage for Egypt Real Estate Price Prediction | |
| # ========================================================== | |
| from transformers import pipeline | |
| HF_MODEL_ID = "migoamr/savesta" | |
| regressor = pipeline("text-classification", model=HF_MODEL_ID) | |
| def predict_price(area_m2, rooms, bathrooms, description, location, property_type): | |
| text_input = f"Area: {area_m2} sqm, Rooms: {rooms}, Bathrooms: {bathrooms}. Description: {description}. Location: {location}. Type: {property_type}." | |
| result = regressor(text_input) | |
| predicted_price = result[0]['score'] | |
| return predicted_price | |
| if __name__ == "__main__": | |
| price = predict_price( | |
| area_m2=180, | |
| rooms=3, | |
| bathrooms=2, | |
| description="Luxury apartment with panoramic views", | |
| location="Fifth Settlement, New Cairo", | |
| property_type="Apartment" | |
| ) | |
| print(f"🏠 Predicted Property Price: {price:,.0f} EGP") | |