Update use_this_model.py with latest SVC model and verify Hub availability

- Updated model filename to uts2017_sentiment_20250928_131716.joblib
- Added error handling for model download verification
- Added model type information (SVC) in output
- Updated performance metrics (71.72% accuracy)
- Verified model is successfully published and accessible on Hugging Face Hub

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <[email protected]>

use_this_model.py

@@ -33,16 +33,23 @@ def predict_text(model, text):
 
 def load_model_from_hub():
     """Load the pre-trained Pulse Core 1 banking aspect sentiment model from Hugging Face Hub"""
-    filename = "uts2017_sentiment_20250928_122636.joblib"
+    filename = "uts2017_sentiment_20250928_131716.joblib"
     print("Downloading Pulse Core 1 (Vietnamese Banking Aspect Sentiment) model from Hugging Face Hub...")
 
-    model_path = hf_hub_download("undertheseanlp/pulse_core_1", filename)
-    print(f"Model downloaded to: {model_path}")
-
-    print("Loading model...")
-    model = joblib.load(model_path)
-    print(f"Model loaded successfully. Classes: {len(model.classes_)} aspect-sentiment combinations")
-    return model
+    try:
+        model_path = hf_hub_download("undertheseanlp/pulse_core_1", filename)
+        print(f"Model downloaded to: {model_path}")
+
+        print("Loading model...")
+        model = joblib.load(model_path)
+        print(f"Model loaded successfully. Classes: {len(model.classes_)} aspect-sentiment combinations")
+        print(f"Model type: {type(model.named_steps['clf']).__name__}")
+        return model
+    except Exception as e:
+        print(f"Error downloading model: {e}")
+        print("This might mean the model file hasn't been uploaded to Hugging Face Hub yet.")
+        print("Please check the repository: https://huggingface.co/undertheseanlp/pulse_core_1")
+        raise
 
 
 def predict_banking_examples(model):
@@ -144,7 +151,7 @@ import joblib
 
 # Download and load Pulse Core 1 model from HuggingFace Hub
 model = joblib.load(
-    hf_hub_download("undertheseanlp/pulse_core_1", "uts2017_sentiment_20250928_122636.joblib")
+    hf_hub_download("undertheseanlp/pulse_core_1", "uts2017_sentiment_20250928_131716.joblib")
 )
 
 # Make prediction on banking text
@@ -197,9 +204,11 @@ def main():
         print("\nDemonstration complete!")
         print("\nPulse Core 1 model is available on Hugging Face Hub:")
         print("- Repository: undertheseanlp/pulse_core_1")
-        print("- Model file: uts2017_sentiment_20250928_122636.joblib")
+        print("- Model file: uts2017_sentiment_20250928_131716.joblib")
         print("- Task: Vietnamese Banking Aspect Sentiment Analysis")
         print("- Classes: 35 aspect-sentiment combinations")
+        print("- Model type: Support Vector Classification (SVC)")
+        print("- Test accuracy: 71.72%")
 
     except ImportError:
         print("Error: huggingface_hub is required. Install with:")