This model is a fine-tuned version of the Qwen3-1.7B-Base large language model, developed by the Qwen Team at Alibaba Cloud, tailored for cybersecurity red teaming tasks. It leverages the Parameter-Efficient Fine-Tuning (PEFT) library to adapt the base model for generating and understanding manual commands relevant to red teaming and penetration testing. The fine-tuning process utilized the darkknight25/redteam_manualcommands dataset, focusing on enhancing the model’s ability to generate contextually accurate and secure command sequences for cybersecurity applications. The model excels in tasks such as crafting penetration testing commands, simulating adversarial scenarios, and assisting in vulnerability assessments. — Developed by: [Sunnythakur] — Shared by [optional]: [sunny thakur] — Model type: Transformer-based large language model (causal/autoregressive) — Language(s) (NLP): English (en) — License: mit — Finetuned from model [optional]: Qwen/Qwen3-1.7B-Base — Repository: https://huggingface.co/darkknight25/REDTEAM_GPT This model is designed for direct use by cybersecurity professionals, red teamers, and penetration testers. It can generate and interpret manual commands for…
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: darkknight25
Теги: peft, cyber, redteam, conversational, en
Лайков: 4 | Загрузок: 94
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
