A clean, distilled supervised fine-tuning dataset for security-focused language models. Built for authorized red-team, penetration-testing, and LLM-security research, and used to train RedSec-7B and RedSec-14B on Hugging Face.
Most security instruction datasets pair prompts with raw, templated payloads. Fine-tuning on those teaches a model the format but fills it with noise. This one flips that: every answer… See the full description on the dataset page:
https://huggingface.co/datasets/sahilempire/redsec-distill-sft-v1.
