Downloads · 30 days
35
5% of all-time downloads
UCSB-SURFI/TermiGen-32B
TermiGen-32B is a text generation model from UCSB-SURFI. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
TermiGen-32B achieves 31.3% pass@1 on TerminalBench 1.0, establishing a new open-weight state-of-the-art and surpassing proprietary models like o4-mini with Codex CLI (20.0%).
Downloads · 30 days
35
5% of all-time downloads
All-time downloads
674
Public
Parameters
1.1M
65.5 GB on disk
Likes
4
Public
Click a slice to open those files.
.safetensors65.5 GB · 100%
From the Hugging Face model README
TermiGen-32B achieves 31.3% pass@1 on TerminalBench 1.0, establishing a new open-weight state-of-the-art and surpassing proprietary models like o4-mini with Codex CLI (20.0%).
📄 Paper: TermiGen: High-Fidelity Environment and Robust Trajectory Synthesis for Terminal Agents
💻 Environments: https://github.com/ucsb-mlsec/terminal-bench-env
🧪 Benchmark: https://github.com/laude-institute/terminal-bench
This model is fine-tuned from Qwen2.5-Coder-32B-Instruct using the TermiGen pipeline, which synthesizes high-fidelity training data through two phases:
Phase I: Environment Synthesis
Phase II: Error-Correction Trajectory Collection
Training Hyperparameters:
Dataset Statistics:
| Benchmark | Pass@1 |
|---|---|
| TerminalBench 1.0 | 31.3% |
| TerminalBench 2.0 | 18.0% |
We implemented a minimal BashAgent framework based on TerminalBench for agentic terminal execution. The agent interacts with Docker containers via bash shell, generating ReAct-style responses at each turn.
For detailed usage and integration examples, please refer to our GitHub repository.
@article{zhu2026termigen,
title={TermiGen: High-Fidelity Environment and Robust Trajectory Synthesis for Terminal Agents},
author={Zhu, Kaijie and Nie, Yuzhou and Li, Yijiang and Huang, Yiming and Wu, Jialian and Liu, Jiang and Sun, Ximeng and Yin, Zhenfei and Wang, Lun and Liu, Zicheng and Barsoum, Emad and Wang, William Yang and Guo, Wenbo},
journal={arXiv preprint arXiv:2602.07274},
url={https://arxiv.org/abs/2602.07274},
year={2026}
}
Apache 2.0 (inherited from Qwen2.5-Coder base model)
Contact: Kaijie Zhu ([email protected])