Upload folder using huggingface_hub

app.py

@@ -95,6 +95,7 @@ def predict_churn_batch():
 
     # Make predictions for all properties in the DataFrame (get log_sales)
     predicted_log_sales = model.predict(input_data).tolist()
+    print("Raw predictions:", predicted_log_sales)
 
     safe_log_sales = np.clip(predicted_log_sales, -100, 100)
     predicted_sales = [round(float(np.exp(log_price)), 2) for log_price in safe_log_sales]