| # Cybersecurity LLM Indic | |
| ## Model Card | |
| ### Overview | |
| We present **Cybersecurity LLM Indic**, a large language model fine-tuned specifically for cybersecurity purposes. This model has been trained on a curated dataset containing cybersecurity data, tips, and guidelines from various Indian government sources. The fine-tuning process involved approximately 3,000 rows of data, ensuring that the model is well-versed in the nuances of cybersecurity within the Indian context. | |
| ### Base Model | |
| The base model used for this fine-tuning process is **Navarasa 2.0 2B Gemma Instruct**. This base model is renowned for its versatility and robustness, making it an excellent foundation for building a specialized cybersecurity model. | |
| ### Training Data | |
| The training dataset comprises a diverse collection of cybersecurity-related information, including: | |
| - Guidelines and advisories from Indian government agencies | |
| - Best practices for securing information systems and networks | |
| - Tips for individuals and organizations to safeguard against cyber threats | |
| - Case studies and real-world examples of cybersecurity incidents and responses | |
| ### Training Procedure | |
| The model was fine-tuned using the following procedure: | |
| - **Data Preparation:** The raw data was cleaned and preprocessed to ensure high-quality input for training. This involved removing duplicates, correcting formatting issues, and standardizing terminology. | |
| - **Fine-Tuning:** The fine-tuning process involved training the model on the prepared dataset for several epochs, optimizing for performance on cybersecurity-related tasks. | |
| - **Evaluation:** The model was evaluated on a separate validation set to ensure its accuracy and relevance in providing cybersecurity advice and guidelines. | |
| ### Use Cases | |
| **Cybersecurity LLM Indic** can be utilized in various scenarios, including: | |
| - **Education and Training:** Providing comprehensive and accurate cybersecurity training materials. | |
| - **Advisory Services:** Offering real-time cybersecurity advice and best practices. | |
| - **Policy Development:** Assisting policymakers in drafting effective cybersecurity policies. | |
| - **Incident Response:** Guiding organizations in responding to cybersecurity incidents. | |
| ### Limitations | |
| While **Cybersecurity LLM Indic** is a powerful tool for cybersecurity applications, it has certain limitations: | |
| - **Domain-Specific Knowledge:** The model is specialized for cybersecurity within the Indian context and may not perform as well on general or international cybersecurity issues. | |
| - **Data Limitations:** The training data consists of approximately 3,000 rows, which, while substantial, may not cover every possible cybersecurity scenario. | |
| - **Continuous Learning:** Cybersecurity is a rapidly evolving field, and the model may need periodic updates to stay current with new threats and best practices. | |
| ### Ethical Considerations | |
| The model was developed with a strong emphasis on ethical considerations, including: | |
| - **Privacy:** Ensuring that the training data does not contain sensitive or personally identifiable information. | |
| - **Bias Mitigation:** Efforts were made to minimize biases in the training data to ensure fair and unbiased advice. | |
| ### License | |
| This model is licensed under the [Apache-2.0 License](LICENSE). | |
| ### Contact Information | |
| For more information or to provide feedback, please contact the development team at [contact email]. | |
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