metadata
license: apache-2.0
datasets:
- TIGER-Lab/BrowserAgent-SFT-Data
language:
- en
base_model:
- Qwen/Qwen2.5-7B-Instruct
metrics:
- success_rate
- trajectory_f1
tags:
- agent
- browser
- web
- sft
Model
We release the SFT (Supervised Fine-Tuned) model used in BrowserAgent, based on Qwen/Qwen2.5-7B-Instruct.
This model learns structured web-browsing behaviors—such as click, type, scroll, read, submit—from human-style demonstrations and produces schema-constrained action sequences for browser environments.
Paper
BrowserAgent: Building Web Agents with Human-Inspired Web Browsing Actions
Project Page
https://tiger-ai-lab.github.io/BrowserAgent/
Code
https://github.com/TIGER-AI-Lab/BrowserAgent
Sample Usage
hf download TIGER-Lab/BrowserAgent-SFT --local-dir ./models/browseragent-sft --repo model
Citation
@misc{yu2025browseragentbuildingwebagents,
title={BrowserAgent: Building Web Agents with Human-Inspired Web Browsing Actions},
author={Tao Yu and Zhengbo Zhang and Zhiheng Lyu and Junhao Gong and Hongzhu Yi and Xinming Wang and Yuxuan Zhou and Jiabing Yang and Ping Nie and Yan Huang and Wenhu Chen},
year={2025},
eprint={2510.10666},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2510.10666},
}