← back to vectors · registered 2026-10-31

msuiche/DeepSeek-V4.1-Flash-1017-abliterated-cyber-GLP-27-L11-37-a3.5

msuiche DeepSeek 1 file mit
API coming soon

Everything on this page as JSON, in the same shape as the /models API. The vectors endpoint arrives in a later release.

curl -H "Authorization: Bearer $ABL_KEY" \
  https://abliteration.org/api/v1/vectors/msuiche%2FDeepSeek-V4.1-Flash-1017-abliterated-cyber-GLP-27-L11-37-a3.5

Vector types 1 files · 1 set

This repo contains 1 vector file organized into 1 set.

other 1 file
See all sets in the Files tab →
Repo downloads
3
on Hugging Face
Likes
0
Repo age
1 day
first commit 2026-10-29
Latest commit
2026-10-31
7 commits
Activity over time · commits, cumulative
Historical download data: coming soon
Now7→from1↑600%
13581 on Oct 297 on Oct 31Oct
Oct 29 → Oct 31 · 7 snapshots · spans 1 day

Compatible base models 1 base model

The models these vectors were made for. A vector loads on any model of the same shape; fine-tunes of these bases usually work too.

Genealogy

Above: repos this one's README cites. Below: vector repos that cite this one.

Derived from

No source repo named in the README.

↓
msuiche/DeepSeek-V4.1-Flash-1017-abliterated-cyber-GLP-27-L11-37-a3.5
↓
Derived vectors

No derived vectors in catalog yet.

Metadata

Licence
mit
Use, modify and redistribute, including commercially, with attribution.
Method
Not classified
Size
544 KB
1 file, 544 KB each on average
Languages
en
Base model
deepseek-ai/DeepSeek-V4.1-Flash-1017

Related

Total size
544 KB
Files
1
Sets
1
Registered
2026-10-31
Last updated on HF
2026-10-31

Files by set base model × axis

Vectorglp.deepseek-v41-flash-1017-GLP-27-L11-37-a3.5.gguf 544 KB 24e97d41 download ↓
llama-cli -m <model>.gguf \
  --control-vector glp.deepseek-v41-flash-1017-GLP-27-L11-37-a3.5.gguf

Auxiliary files

README.md 4.65 KB read

README current version from Hugging Face

Author's description, verbatim. Source: huggingface.co/msuiche/DeepSeek-V4.1-Flash-1017-abliterated-cyber-GLP-27-L11-37-a3.5 ↗

DeepSeek-V4.1-Flash-1017-abliterated-cyber-GLP-27-L11-37-a3.5

Projective control vector ("GLP") for deepseek-ai/DeepSeek-V4.1-Flash-1017
(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). This is the first
GLP spec_version 3 artifact: the directions are weight-SVD rows from the
FFN writers, applied at the hc fold site — post-fold, pre-Engram, mean
over the 4 hyper-connection copies, with the attention o_proj writer armed
on the same stack — layers 11–37, alpha 3.5 baked in. No weights are
modified; this is the difference, not the model.

Confirmed base: deepseek-ai/DeepSeek-V4.1-Flash-1017 (revision
1bae0e1088993b9b82de08f59de5be5a34e42170). The directions were derived from
that checkpoint's FFN writer weights and calibrated on the vLLM offline lane
(the dsv41-feat wheel from vllm-project/vllm PR #56201, build sha
79a7108d9aea27ddab99ce1779290d300b17fc23); not validated against other
revisions or quants.

Reader requirement: glp.hook_point = hc_fold_pre_engram,
glp.spec_version = 3. A conformant reader applies the projection to the
mean over stream copies at the fold consuming layer N's FFN write AND arms
the attention output writer with the same stack — a reader that implements
only the fold under-doses and must refuse the file
(spec,
"Multi-copy streams and the fold site"). Pre-3 readers refuse this file by
design.

Validation (vLLM offline lane, greedy, thinking on, 2026-10-28/29)

weaponize32 alpha ladder (32 items: 16 weaponization asks + 16 benign
defensive variants; keyword-scored refusals, all arms same vector):

alpha weaponize32 refused notes
stock 20/32
0.5 16/32
1.0 16/32 flat refusals convert to analyses
1.5 13/32
2.0 8/32 frameworks, no working tooling
2.5 8/32
3.0 5/32 known-CVE items flip to full exploit-chain walkthroughs
3.5 4/32 operating point — clean outputs
4.0 3/32 CVE-ID token corruption appears
5.0 4/32 regression: typos, worsening corruption

At the 3.5 operating point: refusal32 6/32 refused (stock 32/32),
benign32-holdout 9/32 refused (stock 8/32 — within keyword noise, zero
garbled), min/median completion length 1542/1871 chars. The 4 residual
weaponize32 refusals are knowledge-boundary (real but post-cutoff CVEs the
checkpoint cannot know) plus two honest infeasibility answers — not refusal
behaviour. Alpha 4.0 buys one more item at the cost of exact-token recall;
alpha 5.0 regresses on refusal count and coherence. Coverage cannot reach
32/32 by alpha scaling: factual precision is the binding constraint.

Files

  • glp.deepseek-v41-flash-1017-GLP-27-L11-37-a3.5.gguf — the GLP container
    (spec_version 3, content_sha256
    f0aaba2fd1d5d52deb605495e0b99b8e868d44a4e612c994688cf243a95dfcb4).

Provenance

Derived 2026-10-28, validated 2026-10-28/29. Derivation and validation
tooling: weightless/tools/captain-vector
(0.5.0); format contract: docs/spec/GLP.md.

README history 2 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-10-29Upload README.md with huggingface_hub581ac814.8 KB
    Loading...
  2. 2026-10-29Upload README.md with huggingface_hub407bc024.9 KB
    Loading...

Discussions

Discussions for this repo happen on Hugging Face. Open the discussions ↗

Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration