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msuiche/GLM-5.3-abliterated-GLP-77

msuiche Glm GGUF
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Response includes
  • classification m8
  • files 3
  • author_summary 26 models
  • readme_text full
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Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

Applied on top of direct removal inherited from the base model.
Confidence
MEDIUM
Inherited from base model
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • 'abliterated' in name/tags
  • is_gguf=1
  • assume M1 (base ablation) + M8 (GGUF quant) - default when producer unknown
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
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Model age
6w ago
created 2026-08-30

Metadata

License
mit
Tags
gguf control-vector glp abliteration refusal-direction license:mit region:us

Related

Total size
1.81 MB
Files
3
Quantizations
1
Registered
2026-08-30 02:03
Last updated on HF
2026-08-30 01:33

Files by quantization

Auxiliary files 3 files 1.81 MB
GLM-5.3-abliterated-GLP-77-L1-77-a1.0.gguf 1.81 MB ******** download
README.md 3.41 KB a555a43d download
.gitattributes 1.56 KB 3204b615 download

README current version from Hugging Face


license: mit
tags: [control-vector, glp, abliteration, refusal-direction]

GLM-5.3 — abliterated refusal direction (GLP-77)

A GLP control vector (GGUF Layer Projection, glp.mode=project) for
GLM-5.3 (753B MoE, arch
glm_moe_dsa: MLA + DeepSeek-sparse attention). 77 per-layer unit directions
over the post-layer residual stream (hidden 6144 — no hyperconnection widening
on this arch), layers 1-77, fp32. No model weights are modified; a conforming
reader applies h <- h - alpha * (h . d) d at the post-layer residual stream
(the deepseek_v2 decomposed convention: the stream is hidden_states + residual).

Derived 2026-08-30 on the NVFP4 deployment (RadixArk/GLM-5.3-NVFP4,
marlin MoE backend, vLLM 0.28.0, 8xH100) with the vLLM capture lane
(activation probe on deepseek_v2.py), difference-of-means over the
AdvBench-32 vs Alpaca-32 contrast, per-layer structure, last-token pooling.
Every shipped layer clears a held-out vs shuffled-label null gate (>=5x; peak
layers 48-55 sit at ~60x). Methodology + code:
refusal-research/experiments/20260829-glm53-flagship.

Measured effect (NVFP4, greedy, max 1400 new tokens, n=32 per suite)

GLM-5.3 thinks by default (template = max reasoning effort); completions were
read in full (content + reasoning). Two scorers are reported: the repo
phrase-classifier on the full completion, and an answer-audited count that
splits at </think> and applies extended GLM decline phrasing (the stock
scorer misses "I'm not able to provide").

alpha refusal32 delivered (repo scorer) refusal32 (answer-audited) cyber32 benign32 capability12
0.0 (stock) 1/32 1/32 18/32 31/32 12/12
1.0 (shipped default) 12/32 6/32 32/32 32/32 12/12
1.5 9/32 6/32 29/32 30/32 12/12

Null control (METHODOLOGY §11): 77 random unit vectors, same magnitude, seed
1337, at alpha=1.0 under the same protocol: refusal32 1/32 — identical to
stock
. The effect is the direction, not the dose.

Honest reading: the cyber cluster saturates (18/32 -> 32/32 at alpha=1.0) with
benign and capability untouched. The refusal32 physical-harm/petty-crime
cluster moves from 1/32 to 6-12/32 depending on scorer; the model's long
reasoning re-litigates borderline items at length (11/32 completions still hit
the 1400-token cap mid-thought at alpha=1.0 — those count as not-delivered
here). This is a real, null-gated effect, not a 32/32 claim. For reference,
the baked-weight CRACK release claims 0% refusal at high/max reasoning effort
on HarmBench; the steering counterpart does not reproduce that on refusal32,
and publishes its protocol so the difference is measurable rather than
rhetorical.

Usage

Serve the stock checkpoint (e.g. the RadixArk NVFP4 build) with a GLP-aware
runtime (vLLM hotfix enforcing glp.mode=project, or llama.cpp's
control-vector reader). alpha is a runtime parameter, never folded into the
vector; alpha_default=1.0 is the measured peak on refusal32 (1.5 over-projects
on this suite).

Note: the RadixArk checkpoint declares an fp8 KV-cache scheme that no sm90
sparse-MLA backend accepts; delete quantization_config.kv_cache_scheme from
config.json when serving on Hopper (bf16 KV).

Content SHA-256 (tensor bytes): 5837bcb5fc43a72416a71de0b6aca7c3d2ae7bbb9379eff9bf5bdfcc8179a225

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