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JingyuanHuang
Available on FriendliAI
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Model Details
Model Provider
JingyuanHuang
Model Tree
Qwen/Qwen3.5-9B
Input Modalities
Output Modalities
Supported Functionality
This model is intended for GUI grounding research and evaluation. It takes a GUI screenshot and a natural-language instruction, then predicts the target screen coordinate.
python
from transformers import AutoModelForMultimodalLM, AutoProcessorimport torchmodel_id = "JingyuanHuang/GUI-RD-9B"processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)model = AutoModelForMultimodalLM.from_pretrained(model_id,dtype=torch.bfloat16,device_map="auto",trust_remote_code=True,)
Depending on your installed Transformers version, the concrete auto-model class for Qwen3.5 may differ. For older Transformers releases, use torch_dtype=torch.bfloat16 instead of dtype=torch.bfloat16. The repository provides standard Transformers config, tokenizer, processor, and safetensors weights.
bibtex
@misc{huang2026trustrightteacherqualityaware,title={Trust the Right Teacher: Quality-Aware Self-Distillation for GUI Grounding},author={Jingyuan Huang and Zuming Huang and Yucheng Shi and Tianze Yang and Xiaoming Zhai and Wei Chu and Ninghao Liu},year={2026},eprint={2606.18101},archivePrefix={arXiv},primaryClass={cs.AI},url={https://arxiv.org/abs/2606.18101},}