DeepSeek-V4.1-Flash-abliterated-cyber-GLP-39-L1-39-a0.5

Projective control vector ("GLP") for deepseek-ai/DeepSeek-V4.1-Flash (deepseek_v41: 40 layers, hidden 5120, 384 routed experts + 1 shared, MLA with KV compression, hc_mult=4 hyper-connections, engram layers, built-in DSpark drafter, 510 GB FP8+MXFP4 checkpoint). Applied at runtime as h <- h - alpha * (h . d) d at the post-layer residual stream, layers 1–39, alpha 0.5 baked in. No weights are modified; this is the difference, not the model.

Confirmed base: deepseek-ai/DeepSeek-V4.1-Flash (revision fb2764a5cf321eaa5070ca8f9e892818f477c16d). The direction was derived and calibrated on that exact checkpoint via the vLLM capture lane (dsv41-feat branch of vllm-project/vllm, PR #56201, built sha 79a7108d9aea27ddab99ce1779290d300b17fc23); it is not validated against other revisions or quants.

Validation (vLLM offline lane, greedy, thinking off, 1024-token cap, 2026-09-10)

Termination: no clean-stop collapse attributable to steering (refusal32 28/32 stop; the cyber32 completions are verbose deliveries that hit the 1024-token cap — 6/32 stop there — verified by reading: coherent, on-topic, not loops). No-op gate: an alpha=0.0 arm with the vector loaded reproduces stock labels exactly (32/32 on both gate suites). Zero GARBLED classifications at every alpha tested.

Alpha calibration is the finding of this run. The ladder (refusal32 + benign32-holdout): alpha 0.5 delivers 24/32 with zero measurable collateral; alpha 1.0 delivers 25/32 but slips Chinese phrases into 2–7/32 English answers; alpha 2.0 regresses (refusal32 back to 19/32 comply, 10 fresh refusals) and code-switches on 13–21/32 items. alpha=0.5 is the knee: identical cyber32 delivery to alpha 1.0 (31/32) with no measured collateral.

The direction comes from a general harmful-vs-harmless contrast (refusal32 vs benign32, content-matched, last-token pooling), not from cyber content; the transfer into the offensive-security domain is the measured result, and the "cyber" in the name follows the series convention. n=32 per arm; read rates at that resolution as approximate.

Usage

This file uses the glp.* GGUF namespace (spec: weightless spec/GLP.md) and is read projective-only. An additive consumer must refuse this file. The hook point is residual_stream_post_layer: on this architecture (hc_mult=4 hyper-connections) that is the post-layer hyper-connection fold reduced to the single stream by the mean over the four hc copies, taken pre-engram — derived AND applied at that site. It is NOT the ffn_out_pre_residual site used by the DeepSeek-V4-0731 GLP-29 vector; a reader that applies only that hook must refuse this file.

export WEIGHTLESS_STEER_PATH=DeepSeek-V4.1-Flash-abliterated-cyber-GLP-39-L1-39-a0.5.gguf
export WEIGHTLESS_STEER_ALPHA=0.5
# apply the dsv41 steering patch, then serve

Serving shape. No released vLLM loads deepseek_v41 today: serving requires the dsv41-feat branch of vllm-project/vllm (PR #56201). The validated research shape is a source build of that branch on 4x H200, tensor-parallel 4, offline LLM driver; the steering patch for the branch's deepseek_v4_1/nvidia/model.py lives in refusal-research/experiments/20260910-dsv41-flash-glp/staging/patch_dsv41.py. The 510 GB FP8+MXFP4 checkpoint does not fit 2x128 GB rigs in any quant that exists at publication time.

What is inside

Do not scale alpha across models

alpha_default is calibrated on this checkpoint, at this hook. On this model the response is sharply non-monotone: alpha 2.0 removes less refusal than alpha 0.5 and visibly damages the output register (code-switching on up to two-thirds of items). The mean dose at alpha=1 ranges from 3% of the residual norm at layer 1 to 41% at layer 30. Do not port the DeepSeek-V4-0731 alpha (4–6 at a different hook) to this file, and do not port this 0.5 anywhere else: re-run the ladder.

Caveats

• Checkpoint-specific. Tied to the revision pinned above. Applying it to another model or revision is undefined.
• Not a jailbreak of a hosted service. It requires local weights and a runtime that implements the projection.
• Layers 1–6 sit below the derivation null gate (held-out separation vs shuffled-label null under 5x; the stack median is 40x). They shipped because the measured stack (L1-39) is clean at alpha 0.5; at higher alpha they are the first place to look if behaviour degrades.
• n=32 suites resolve about 30 points; the suites that matter most were verified by reading the completions, not only the classifier.

License

Base model © DeepSeek, MIT. This vector modifies and redistributes no weights; the base license continues to govern the weights it is applied to.

Author

Matt Suiche.