Hey everyone, I'm releasing **Qwen3.8-cyber-RedTeam-Surgical-Abliterated (27B)**, an unconstrained foundation engine fine-tuned specifically for cybersecurity engineers, authorized red- team operations, and memory exploitation research. Tired of frontier models refusing to dissect vulnerable kernel dispatch routines or rejecting benign fuzzing/audit payloads with moralizing lectures? This model addresses that directly. ### Key Highlights: * **Architecture**: 27B Qwen 3.5 Hybrid SSM (48 Linear-Attention layers + 16 Full-Attention layers) with 75% active KV-cache reduction (runs full 256K contexts on single GPUs without OOM). * **Context Window**: Native 256K context support (RoPE $\theta = 10^7$). * **Surgical Abliteration**: Refusal direction centroids were mathematically removed via residual stream orthogonalization—zero preachy refusals while rigorously preserving deterministic C/assembly syntax and reasoning. * **Precision**: Sharded native FP8 (F8_E4M3, block size 128x128) fitting on single 32GB/48GB/80GB GPUs. * **Agentic Ready**: Native multi-step tool-calling support, zero-overhead RadixAttention prefix caching via SGLang. ### 1-Command Quickstart: git clone https://huggingface.co/medismera/Qwen3.8-cyber-RedTeam-Surgical-Abliterated cd Qwen3.8-cyber-RedTeam-Surgical-Abliterated bash deploy.sh **Model Card & Weights**: [medismera/Qwen3.8-cyber-RedTeam-Surgical-Abliterated](https://huggingface.co/medismera/Qwen3.8-cyber-RedTeam-Surgical-Abliterated) Feedback and bug reports from the community are warmly welcome!   submitted by   /u/Least_Dog_8556 [link]   [comments]