Update README.md

README.md

@@ -30,6 +30,7 @@ The model was trained on a custom GDPR violation dataset containing real violati
 - 2,412 cases total (2,058 violations, 354 non-violations)
 - Features include affected data volume, countries, industry sectors, data categories, data processing basis, GDPR clauses, and various violation indicators
 - All categorical features were converted to text descriptions for the transformer model
+- Dataset link: https://huggingface.co/datasets/JQ1984/GDPRcasedata
 
 ## Training Methodology
 
@@ -74,4 +75,13 @@ probabilities = outputs.logits.softmax(dim=-1)
 predicted_class = outputs.logits.argmax(dim=-1).item()
 
 print(f"Predicted class: {predicted_class}")
-print(f"Class probabilities: {probabilities[0].tolist()}")
+print(f"Class probabilities: {probabilities[0].tolist()}")
+```
+
+## Contact
+
+For questions, feedback, or collaboration opportunities, please contact:
+Jacques Qiu(邱耿航)
+Email: jonstark186@gmail.com
+GitHub: JacquotQ
+LinkedIn: https://www.linkedin.com/in/jacques-qiu-50477b266/