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--- |
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license: apache-2.0 |
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datasets: |
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- TIGER-Lab/BrowserAgent-Data |
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language: |
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- en |
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base_model: |
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- Qwen/Qwen2.5-7B-Instruct |
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metrics: |
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- success_rate |
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- trajectory_f1 |
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tags: |
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- agent |
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- browser |
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- web |
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- sft |
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--- |
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## Model |
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We release the **SFT (Supervised Fine-Tuned)** model used in **BrowserAgent**, based on `Qwen/Qwen2.5-7B-Instruct`. |
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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. |
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- **Base:** Qwen2.5-7B-Instruct |
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- **Objective:** Next-token prediction on normalized, schema-validated browsing trajectories |
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- **Format:** JSON-like structured actions (compatible with BrowserAgent runtime) |
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## Data |
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The SFT data includes: |
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- Human and assisted browsing demonstrations |
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- Canonicalization under a unified action schema |
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- Filtering and de-duplication to ensure validity and safety |
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## Code |
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<https://github.com/TIGER-AI-Lab/BrowserAgent> |
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## Sample Usage |
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```bash |
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hf download TIGER-Lab/BrowserAgent-SFT --local-dir ./models/browseragent-sft --repo model |
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