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View details ↗frankenmoe
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View details ↗Qwen3.8-27B-abliterated
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View details ↗GGUF builds of the **offensive-security / agentic tool-calling** merged model hotdogs/Qwen3.8-27B-abliterated-cyber-preview (the cyber LoRA merged into the abliterated base at **scale 1.0**, with the **MTP head preserved**). All files are imatrix-quantized and are ready to run in llama.cpp with native **self-speculative (MTP) decoding**. > For **authorized security research and red-teaming** only — this model will > not refuse and may emit exploit instructions. Use only on systems you own or > are explicitly authorized to test. Apache-2.0. The quantized files were produced with an **imatrix** (see `...-imatrix.dat`) computed from the bf16 master — required for the 4-bit IQ files and improving low-bit quality.
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View details ↗GGUF quantization of **hotdogs/Qwen3.8-27B-abliterated** — the training-free abliterated (refusal-removed) build of `Qwen/Qwen3.8-27B` — converted for **llama.cpp** with the **MTP (Multi-Token Prediction) head preserved**. > **Status: testing / development.** This is an early GGUF upload for evaluation. It has **not yet been calibrated with an imatrix** — the low-bit `Q4_K_M` quality is expected to improve once an imatrix is added (see *Roadmap*). Feedback welcome. These `-mixed` quants use a **hybrid precision recipe** to get closer to the f16 reference: the token-embedding and all output tensors are kept at `q8_0` while the rest of the network is quantized to the base level, and they are built with an **imatrix** (CPU calibration) — `Q4_K_M-mixed` and `Q6_K-mixed`.
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View details ↗Qwen35B-Agent-R2-Abliterated
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View details ↗**BoldingBuilds' abliterated Bonsai 2 v2, with two SVD-LoRAs merged in at 0.4 each:** `hotdogs/swift_unc_qwen3.8-27B_lora` (abliteration + Swift-1.5 reasoning-efficiency) and `hotdogs/thinkingcap_qwen3.8-27B_svd_lora` (ThinkingCap token-efficient reasoning). Same 27B ternary runtime as the base — **PQ2_0 packing, Hadamard latent, MTP head, 262,144-token context**, ~7.6 GB on disk. Vision projector included. > ⚠️ **This file needs PrismML's llama.cpp fork.** PQ2_0 does **not** load in mainline llama.cpp, Ollama, LM Studio or llama.app. See Requirements.
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