Fine-tune of unsloth/Qwen2.5-Coder-1.5B-Instruct that flags AI slop (over-defensive code, redundant comments, filler docstrings, emoji logs, placeholder TODOs…) in Python pull-request hunks and returns JSON findings. Built with tidypr. Use it in a PR: LoRA fine-tune (Unsloth, QLoRA) on a mix of: - inline review comments from humans on AI-agent pull requests (AIDev), and review comments from CodeReviewer, turned into labels by a Qwen2.5-Coder-7B teacher - hunks reviewers accepted without comment (CodeReviewer) - synthetic slop injected into human-written Python (CPython standard library) Weights: Apache-2.0, same as the base model unsloth/Qwen2.5-Coder-1.5B-Instruct. Code: MIT (tidypr). The…
Independent publisher
Harsh
bunnyweb
Models in Library1
Datasets in Library0
Models on Hugging Face1
Followers—
Compare the published evidence
This profile connects the 1 model and dataset record shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.
Reported licenses: apache-2.0. Open a record to review its specific license and conditions.
Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.