| language: en | |
| library_name: sklearn | |
| tags: | |
| - safety | |
| - guardrail | |
| - content-filtering | |
| - prompt-detection | |
| - machine-learning | |
| license: mit | |
| # Omega Guard - Advanced LLM Prompt Safety Classifier | |
| ## Model Overview | |
| Omega Guard is a sophisticated machine learning model designed to detect potentially harmful or malicious prompts in natural language interactions. | |
| ## Technical Specifications | |
| - **Python Version**: 3.11.9 | packaged by conda-forge | (main, Apr 19 2024, 18:36:13) [GCC 12.3.0] | |
| - **Scikit-learn Version**: 1.6.1 | |
| - **NumPy Version**: 1.26.4 | |
| ## Model Capabilities | |
| - Advanced text and feature-based classification | |
| - Comprehensive malicious prompt detection | |
| - Multi-level security pattern recognition | |
| - Scikit-learn compatible Random Forest classifier | |
| ## Use Cases | |
| - Content moderation | |
| - Prompt safety filtering | |
| - AI interaction security screening | |
| ## Licensing | |
| This model is released under the MIT License. | |
| ## Recommended Usage | |
| Carefully evaluate and test the model in your specific use case. This is a machine learning model and may have limitations or biases. | |
| ## Performance Metrics | |
| Please refer to the `performance_report.txt` for detailed classification performance. | |
| ## Contact | |
| For more information or issues, please open a GitHub issue. | |