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Luoberta/Abacus-cve
Abacus-cve is a text generation model from Luoberta. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
Abacus-cve (Live Agent Coder) is a 32B code model fine-tuned on CVE-Factory agent traces for security vulnerability fixing tasks.
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From the Hugging Face model README
Abacus-cve (Live Agent Coder) is a 32B code model fine-tuned on CVE-Factory agent traces for security vulnerability fixing tasks.
Abacus-cve is based on Qwen3-32B and fine-tuned using 4,078 distilled agent traces from ~900 CVE reproduction tasks. The traces were generated using Claude Opus 4.5 with a Mini SWE-Agent harness through the CVE-Factory pipeline.
Fine-tuning yields dramatic improvements across security benchmarks:
| Model | LiveCVEBench | PatchEval | Terminal-Bench | Avg |
|---|---|---|---|---|
| Qwen3-32B (base) | 5.29 | 5.66 | 12.50 | 7.82 |
| Abacus-cve (Ours) | 35.79 | 23.58 | 28.75 | 29.37 |
| Qwen3-Coder-30B | 10.58 | 9.91 | 13.75 | 11.41 |
| Qwen3-Coder-480B | 19.58 | 19.34 | 36.25 | 25.06 |
| MiniMax-M2 | 24.87 | 19.34 | 37.50 | 27.24 |
| Claude Sonnet 4 | 20.11 | 22.64 | 33.75 | 25.50 |
| Claude Sonnet 4.5 | 34.39 | 28.77 | 45.00 | 36.05 |
| Claude Opus 4.5 | 41.27 | 32.08 | 48.75 | 40.70 |
Key findings:
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("Luoberta/Abacus-cve")
tokenizer = AutoTokenizer.from_pretrained("Luoberta/Abacus-cve")
@misc{luo2026cvefactory,
title={CVE-Factory: Scaling Expert-Level Agentic Tasks for Code Security Vulnerability},
author={Xianzhen Luo and Jingyuan Zhang and Shiqi Zhou and Rain Huang and Chuan Xiao and Qingfu Zhu and Zhiyuan Ma and Xing Yue and Yang Yue and Wencong Zeng and Wanxiang Che},
year={2026},
eprint={2602.03012},
archivePrefix={arXiv},
primaryClass={cs.CR},
url={https://arxiv.org/abs/2602.03012}
}