Lily-Cybersecurity-7B-v0.2-GGUF
| Property | Value |
|---|---|
| Parameter Count | 7.24B |
| Base Model | Mistral-7B-Instruct-v0.2 |
| License | Apache-2.0 |
| Training Duration | 24 hours (5 epochs) |
| Hardware Used | 1x A100 GPU |
What is Lily-Cybersecurity-7B-v0.2-GGUF?
Lily-Cybersecurity-7B-v0.2-GGUF is a specialized AI model designed for cybersecurity applications. It's a quantized version of the original Lily model, fine-tuned on 22,000 hand-crafted cybersecurity and hacking-related data pairs. The model combines technical expertise with a friendly, conversational personality to make complex cybersecurity concepts more accessible.
Implementation Details
The model is built on the Mistral-7B-Instruct-v0.2 architecture and has been optimized through GGUF quantization for improved efficiency. The training process involved detailed cybersecurity contexts across multiple domains, with additional LLM processing to enhance response quality and personality.
- Comprehensive coverage of 25+ cybersecurity domains
- Specialized instruction format for consistent responses
- Enhanced with personality traits for engaging interactions
- Optimized through GGUF quantization for better performance
Core Capabilities
- Advanced Persistent Threats (APT) Management
- Cloud Security and Architecture Design
- Digital Forensics and Malware Analysis
- Incident Response and Risk Management
- Network Security and Penetration Testing
- Regulatory Compliance and Legal Considerations
- Social Engineering and Human Factors Analysis
Frequently Asked Questions
Q: What makes this model unique?
Lily combines deep cybersecurity expertise with a friendly, accessible personality. It's been specifically trained on 22,000 cybersecurity scenarios and enhanced with natural conversation abilities, making it particularly effective for both technical and educational use cases.
Q: What are the recommended use cases?
The model is ideal for cybersecurity training, incident response planning, security assessments, and educational purposes. It can assist security professionals, students, and organizations in understanding and implementing security best practices.
