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AltronisSG/judgment-qc-gate-qwen3-4b-GGUF
judgment-qc-gate-qwen3-4b-GGUF is a machine learning model from AltronisSG. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Ready-to-serve quantisation of a 4B LoRA fine-tune that reviews work against one operator's standards and returns a single-line verdict. Built to run as a Stop-hook gate on a live coding agent: a violation verdict blo…
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From the Hugging Face model README
Ready-to-serve quantisation of a 4B LoRA fine-tune that reviews work against one operator's standards and returns a single-line verdict. Built to run as a Stop-hook gate on a live coding agent: a violation verdict blocks the agent's reply and is fed back so it fixes the problem or explains why the verdict does not apply.
These weights are byte-identical to the model running in production on the author's machine.
judgment-qwen3-4b-Q8_0.gguf (4.3 GB)Qwen/Qwen3-4Bllama-server -m judgment-qwen3-4b-Q8_0.gguf \
--host 127.0.0.1 --port 8005 \
--ctx-size 4096 --parallel 1 -ngl 99 -fa 1 \
--jinja --reasoning-budget 0 --no-warmup
--reasoning-budget 0 matters: the fine-tune emits an empty <think></think> block before its verdict
(the corpus contains no reasoning traces). Disable thinking, or strip the block in post-processing.
VERDICT: OK
VERDICT: <TAG> | <one-sentence correction>
VERDICT: ABSTAIN | <what is missing>
<TAG> comes from a closed vocabulary of about 14: VERIFY, NO-OVERCLAIM, HOLD-LINE, SCOPE, SIMPLE,
DESIGN, SAFETY, ROOT-CAUSE, NO-SILENT-FAIL, MAINTAIN, CURRENT, PROACTIVE, CONCERN-MAP,
FULL-BUILD.
Prefix each situation with its phase, pre (plan / approach), during (execution), or post (before
it ships / claiming done):
[phase: post] Assistant cited a CVE number as the relevant vulnerability without
having looked it up anywhere.
VERDICT: VERIFY | You can't cite a CVE without checking it against the real source.
Measured against this exact file while it was serving live, using two fixed probe sets:
| Check | v10 | v8 | v5 |
|---|---|---|---|
| Known violations caught (n=12) | 12 / 12 | 12 / 12 | 12 / 12 |
| False positives on clean situations (n=30) | 0 / 30 | 2 to 3 / 30 | 3 / 30 |
The false-positive count falling to 0/30 tracks the corpus rebalancing: the training set is now about 60 percent compliant-but-risky-looking work, so the model stopped blocking clean situations while still catching every planted violation.
Two honest caveats. Recall is at ceiling on this probe set, which means the probe set is too easy; treat 12/12 as "no obvious misses", not "catches everything". And 30 clean cases is a small set, so read 0/30 as a direction, not a guarantee.
Treat VERDICT: OK as pass and anything else as a correction to act on. Fail open, loudly. If the
gate is unreachable, let the work through and say the gate was down. A quality gate that silently
blocks is worse than no gate.
Built by Altronis. The corpus is one operator's own review history, approved example by example, and generalised to contain no names, figures, or private details.