metadata
license: apache-2.0
datasets:
- TIGER-Lab/BrowserAgent-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.
- Base: Qwen2.5-7B-Instruct
- Objective: Next-token prediction on normalized, schema-validated browsing trajectories
- Format: JSON-like structured actions (compatible with BrowserAgent runtime)
Data
The SFT data includes:
- Human and assisted browsing demonstrations
- Canonicalization under a unified action schema
- Filtering and de-duplication to ensure validity and safety
Code
https://github.com/TIGER-AI-Lab/BrowserAgent
Sample Usage
hf download TIGER-Lab/BrowserAgent-SFT --local-dir ./models/browseragent-sft --repo model