A LoRA adapter for
Qwen/Qwen2.5-Coder-14B-Instruct. It is the Reviewer used by
trace, a research system that
turns known upstream security fixes into merge-ready nixpkgs evidence bundles.
Given a machine-authored security backport patch and the human upstream fix it
claims to reproduce, the adapter emits an accept or reject verdict with a short
grounded rationale. It checks that the backport transcribes the upstream fix,
addresses the stated CVE, keeps the change minimal, and does not invent claims
the artifacts do not support. It is trained to review a patch it did not write,
from a different model family than the one that authored it, so the reviewer and
the patcher never share context.
It is not a general-purpose code reviewer or a vulnerability scanner. It answers
one narrow question inside the trace contract: does this backport match the
ground-truth fix. Outside that setup its verdicts carry no meaning.
QLoRA on the
reviewer-lora-data
corpus: valid review bundles as positives and constructed wrong-patch examples
as negatives, all derived from the trace corpus. Version 1.10 passes the pilot
gate (9/9 canary, 11/11 held-out test).
1from peft import PeftModel
2from transformers import AutoModelForCausalLM, AutoTokenizer
3
4base = "Qwen/Qwen2.5-Coder-14B-Instruct"
5tok = AutoTokenizer.from_pretrained(base)
6model = AutoModelForCausalLM.from_pretrained(base, device_map="auto")
7model = PeftModel.from_pretrained(model, "adastracomputing/reviewer-lora-v1.10")
The review prompt and the surrounding contract live in the trace repository.
Run the adapter with that prompt; a bare instruction will not reproduce the
trained behaviour.
Apache-2.0, matching the base model.