ZeroXClem/Qwen2.5-7B-Qandora-CySec
ZeroXClem/Qwen2.5-7B-Qandora-CySec is a 7 billion parameter model merge based on the Qwen2.5 architecture, combining general question-answering capabilities with specialized cybersecurity expertise. Developed by ZeroXClem using the mergekit framework, it excels in hybrid scenarios requiring both broad knowledge and specific cybersecurity analysis. This model is designed for applications ranging from general Q&A tasks to in-depth cybersecurity analysis, leveraging spherical linear interpolation for optimal blending of its constituent models.
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Model Overview
ZeroXClem/Qwen2.5-7B-Qandora-CySec is a 7 billion parameter model created by ZeroXClem through a mergekit framework, specifically designed to integrate general question-answering (Q&A) abilities with specialized cybersecurity knowledge. It combines bunnycore/QandoraExp-7B for robust Q&A and trollek/Qwen2.5-7B-CySecButler-v0.1 for cybersecurity expertise, using spherical linear interpolation (SLERP) for blending.
Key Capabilities
- Hybrid Intelligence: Seamlessly handles both general knowledge queries and complex cybersecurity-related questions.
- Specialized Cybersecurity: Provides insights and analysis within cybersecurity domains.
- General Q&A: Capable of performing broad question-answering tasks.
- Merge Configuration: Utilizes SLERP with specific parameter adjustments for self-attention and MLP layers, ensuring a balanced contribution from both base models.
Performance Metrics
Evaluations on the Open LLM Leaderboard show an average score of 30.95. Notable scores include 67.73 on IFEval (0-Shot) and 38.72 on MMLU-PRO (5-shot), indicating its proficiency in certain reasoning and understanding tasks.
Good For
- General Q&A Tasks: Answering a wide range of questions.
- Cybersecurity Analysis: Assisting with cybersecurity-specific inquiries and problem-solving.
- Hybrid Scenarios: Ideal for applications that require a blend of general knowledge and specialized cybersecurity insights.