Add Usage example script

usage_example.py

@@ -0,0 +1,58 @@
+"""
+CO-PO Mapping Model - Usage Example
+"""
+
+import pickle
+import numpy as np
+from huggingface_hub import hf_hub_download
+
+def load_model():
+    """Download and load the CO-PO mapping model"""
+    model_path = hf_hub_download(
+        repo_id="Jrine/co-po",
+        filename="co_po_model_complete.pkl"
+    )
+    
+    with open(model_path, 'rb') as f:
+        package = pickle.load(f)
+    
+    return package['model'], package['vectorizer']
+
+def predict_co_po(statement, model, vectorizer):
+    """Predict PO correlations for a CO statement"""
+    # Vectorize
+    vec = vectorizer.transform([statement])
+    
+    # Predict
+    pred = model.predict(vec)[0]
+    pred_rounded = np.clip(np.round(pred), 0, 3).astype(int)
+    
+    return pred_rounded
+
+# Example usage
+if __name__ == "__main__":
+    # Load model
+    print("Loading model...")
+    model, vectorizer = load_model()
+    print("Model loaded!\n")
+    
+    # Example CO
+    co = "Design and implement machine learning solutions for real-world problems"
+    
+    # Predict
+    predictions = predict_co_po(co, model, vectorizer)
+    
+    # Display
+    po_names = ['Engineering Knowledge', 'Problem Analysis', 'Design/Development',
+                'Investigation', 'Modern Tool Usage', 'Engineer and Society',
+                'Environment', 'Ethics', 'Team Work', 'Communication', 
+                'Project Management']
+    
+    levels = ['None', 'Low', 'Medium', 'High']
+    
+    print(f"Course Outcome: {co}\n")
+    print("PO Mapping:")
+    print("-" * 70)
+    
+    for i, (name, score) in enumerate(zip(po_names, predictions), 1):
+        print(f"PO{i:2d} ({name:30s}): {score} ({levels[score]})")