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Senecallm X Qwen2.5 7B CyberSecurity
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Senecallm X Qwen2.5 7B CyberSecurity

Developed by AlicanKiraz0
SenecaLLM is a cybersecurity-specific large language model fine-tuned from Qwen2.5-Coder-7B-Instruct, focusing on the cybersecurity domain and capable of thinking like an expert to assist in solving related problems.
Large Language Model
Safetensors
 EnglishOpen Source License:MIT#Cybersecurity Expert Thinking#Penetration Testing Assistance#Malware Analysis
Downloads 364
Release Time : 12/30/2024

Model Overview

This model underwent approximately 100 hours of training and fine-tuning, specializing in cybersecurity to assist with tasks such as incident response, threat hunting, code analysis, vulnerability development, reverse engineering, and malware analysis.

Model Features

Cybersecurity Expert-Level Thinking
The model is specially trained to think and analyze problems like a cybersecurity expert.
Multi-Domain Coverage
Focuses on various cybersecurity domains including incident response, threat hunting, code analysis, vulnerability development, reverse engineering, and malware analysis.
Anti-Malicious Use Design
The model is fine-tuned to resist potential malicious use scenarios.
High-Performance Computing Support
Training utilized multiple high-performance computing systems including 1x4090, 8x4090, and 3xH100.

Model Capabilities

Cybersecurity Q&A
Incident Response Analysis
Threat Hunting Recommendations
Code Security Analysis
Vulnerability Development Assistance
Reverse Engineering Support
Malware Analysis

Use Cases

Cybersecurity
Incident Response
Assists in analyzing security incidents and providing response recommendations
Threat Hunting
Helps identify and track potential security threats
Vulnerability Analysis
Assists in vulnerability identification and development
Code Security
Code Audit
Analyzes potential security issues in code
Reverse Engineering
Assists in binary code analysis
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