Base model: Qwen/Qwen3-8B
Format: Hugging Face Transformers + Safetensors
Intended domain: web navigation, browser interaction, reasoning-to-action generation

Intended Uses

This model is intended for:

Research on language agents for web environments
Multi-turn prompting with reasoning and action generation
Offline evaluation on browser-task datasets
Experiments involving tool-use and UI-grounded planning

Out-of-Scope Uses

This model is not intended for:

Production autonomy without action validation
Safety-critical or regulated domains
Situations requiring guaranteed factuality or correctness
Fully trusted execution of generated actions

Training Data

This model was fine-tuned on a WEASEL/AgentTrek-style web-agent dataset with message-based interaction trajectories. The underlying trajectories come from yeonjooooni/agenttrek-WEASEL, while the reasoning traces were newly generated using inference from Qwen3-8B.

Training Objective

The fine-tuning objective emphasizes:

following browser-task instructions
producing coherent next actions
grounding outputs in observed state
supporting reasoning-heavy interaction traces

Limitations

The model can generate invalid or non-executable actions
Reasoning traces may sound confident while being wrong
Performance may degrade outside the web-agent data distribution
Prompt wording can materially affect output quality
Additional runtime checks are recommended before action execution

Usage

Transformers

python

from transformers import AutoTokenizer, AutoModelForCausalLM

model_id = "yeonjooooni/Qwen3_8B_WEASEL"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)