CyberSecQwen-4B在網路安全基準測試中匹敵8B競品
阿裡巴巴研究人員發布了cybersecqwen-4b，這是一個40億參數的模型，在保持思科8b模型97.3%準確率的同時，可運行在消費級gpu上。
Hugging Face released CyberSecQwen-4B, a 4-billion parameter model fine-tuned for defensive cybersecurity. The model achieves 97.3% of the CTI-RCM accuracy of Cisco's Foundation-Sec-Instruct-8B and exceeds its CTI-MCQ score by +8.7 points, despite using half the parameters. It runs efficiently on a single 12 GB consumer GPU or a single AMD Instinct MI300X 192 GB instance, enabling local processing of sensitive data like incident reports and malware samples without API calls. The training pipeline used full bf16 precision and FlashAttention-2 on the AMD MI300X.