Lily-Cybersecurity-7B-v0.2
| 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?
Lily-Cybersecurity-7B-v0.2 is a specialized cybersecurity AI assistant built on the Mistral-7B-Instruct-v0.2 architecture. The model has been meticulously fine-tuned using 22,000 hand-crafted cybersecurity and hacking-related data pairs, enhanced with additional context and personality traits to create an engaging and informative cybersecurity expert.
Implementation Details
The model employs a sophisticated fine-tuning approach that combines technical accuracy with conversational fluency. Training was conducted over 5 epochs on an A100 GPU, with careful attention to maintaining the balance between technical precision and accessibility.
- Built on Mistral-7B-Instruct-v0.2 architecture
- Fine-tuned with 22,000 cybersecurity-specific data pairs
- Implements F32 tensor type for precise computations
- Includes comprehensive prompt formatting system
Core Capabilities
- Advanced Persistent Threats (APT) Management
- Cloud Security and Architecture Design
- Digital Forensics and Malware Analysis
- Incident Response and Management
- Network Security and Penetration Testing
- Cryptography and PKI Implementation
- Security Operations and Monitoring
- Regulatory Compliance and Risk Management
Frequently Asked Questions
Q: What makes this model unique?
Lily combines deep cybersecurity expertise with a friendly, accessible personality. The model's training on 22,000 hand-crafted scenarios makes it particularly effective for both technical discussions and practical security guidance.
Q: What are the recommended use cases?
The model is ideal for cybersecurity professionals, IT administrators, and security researchers who need assistance with threat analysis, security architecture design, incident response planning, and security education. It can provide detailed technical explanations while maintaining accessibility for various expertise levels.
