This model was quantized from fdtn-ai/Foundation-Sec-8B to an 8-bit (Q80) GGUF checkpoint using llama.cpp. It retains the cybersecurity specialization of the original 8-billion-parameter model while reducing the memory footprint from approximately 16GB (BF16) to around 8.54GB (Q80) for inference. fdtn-ai/Foundation-Sec-8B-Q80-GGUF is an 8-bit quantized variant of Foundation-Sec-8B** — an 8B-parameter LLaMA 3.1–based model that was continued-pretrained on a curated corpus of cybersecurity-specific text (e.g., CVEs, threat intel reports, exploit write-ups, compliance guides). The base model was originally released on April 28, 2025 under Apache 2.0, and excels at tasks such as: — Threat intelligence summarization (e.g., summarizing CVE details) — Vulnerability classification (mapping CVEs/CWEs to MITRE ATT&CK) — Incident triage assistance (extracting IoCs, summarizing log data) — Red-team simulation prompts and security-workflow generation Rather than re-uploading or replicating the entire training details, please refer to the original model card — Quantization Scheme: 8-bit, «Q80» (8-bit…
Модальности:
Генерация текста
Задача: Генерация текста
Автор: fdtn-ai
Теги: gguf, security, llama, quantization, en, endpoints_compatible
Лайков: 4 | Загрузок: 112
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
