A fine-tuned version of Qwen2.5-3B-Instruct specifically designed for advanced cybersecurity analysis. This model is built to bridge the gap between high-level vulnerability descriptions and low-level exploit code execution. — Developed by: Mohamedabul — License: apache-2.0 — Finetuned from model: unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit — Architecture: 3B parameters (4-bit QLoRA) This qwen2 model was trained 2x faster with Unsloth and Huggingface’s TRL library. To achieve maximum accuracy, the model was fine-tuned on an expansive historical corpus of modern vulnerabilities and exploits, completely uncapped and unfiltered: — NVD CVE Database: Vulnerabilities published between 2020 through 2025. — Exploit-DB: Over 45,000+ real-world exploits directly from Offensive Security. — MITRE CWE: Full weakness classifications, likelihood of exploit, and abstractions. — Total Dataset Size: ~187,700 structured instruction samples. INVALID LANGUAGE PAIR SPECIFIED. EXAMPLE: LANGPAIR=EN|IT USING 2 LETTER ISO OR RFC3066 LIKE ZH-CN. ALMOST ALL LANGUAGES SUPPORTED BUT SOME MAY HAVE NO CONTENT
Модальности:
Генерация текста
Области применения:
Диалог / чат Следование инструкциям
Задача: Генерация текста
Автор: Mohamedabul
Теги: qwen2, text-generation-inference, unsloth, cybersecurity, vulnerability-analysis, exploit-code, conversational, en
Лайков: 3 | Загрузок: 5,740
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
