Intended Use
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.
Loading
from transformers import AutoModelForMultimodalLM, AutoProcessorimport torch model_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.
Citation
@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},}