# 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].

![Cybersecurity LLM Indic](https://cdn-uploads.huggingface.co/production/uploads/64f1a7418ebfe7c68bdd75cd/FeQLOeprf_9yYd_Ne7A4k.png)