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aaardpark/Qwen3.6-27B-abliterated-GGUF

sourceHugging Faceapache-2.0updated 5mo agoView on Hugging Face
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Model Card

Qwen3.6-27B abliterated | aard-Q3

11 GB of Qwen 3.6-27B with the refusal direction surgically removed.

Refusal rate (6 hard prompts)KL vs base on harmless
Base FP166 / 6 = 100%0
abliterated FP16~0 / 6 (1 reframe, 5 comply)0.0056 mean
aard-Q3 (this file)inherits from FP16inherits

For reference: the non-abliterated aard-Q3 hits 47/50 on GSM8K (94%). Abliteration is a rank-1 weight perturbation — capability hit is below quantization noise.

What "abliterated" means

Removed the refusal direction at layer 49 (cohen's d ≈ 7.0 between harmful and harmless prompt activations). One unit vector projected out of every weight that writes to the residual stream — embedtokens, every block's `oproj / outproj` / `downproj` (131 tensors total, ~5 GB of changes out of 54 GB).

Mean KL divergence vs base on 64 harmless Alpaca prompts: 0.0056 (Heretic's "clean" reference is ~0.08 — this is 14× under that).

Run it

bash
huggingface-cli download aaardpark/Qwen3.6-27B-abliterated-GGUF \
  qwen3.6-27B-abliterated-aaardpark-uniform-Q3_K.gguf --local-dir .

llama-cli -m qwen3.6-27B-abliterated-aaardpark-uniform-Q3_K.gguf -ngl 99 -c 32768

Same llama.cpp / runtime requirements as the non-abliterated version (build 8670+, thinking model, budget 2048+ tokens for hard reasoning).

Quick stats

Fileqwen3.6-27B-abliterated-aaardpark-uniform-Q3_K.gguf
Size11 GB
FormatGGUF, uniform Q3_K (3.59 BPW)
Refusal directionlayer 49, rank-1 ortho-projection
Min VRAM16 GB
Throughput~30 tok/s on Apple M-series
Native context262K

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