---
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
```bash
hf download TIGER-Lab/BrowserAgent-SFT --local-dir ./models/browseragent-sft --repo model