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JingyuanHuang/GUI-RD-9B
GUI-RD-9B is a image-text-to-text model from JingyuanHuang. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
This is the GUI-RD checkpoint for Trust the Right Teacher: Quality-Aware Self-Distillation for GUI Grounding.
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From the Hugging Face model README
This is the GUI-RD checkpoint for Trust the Right Teacher: Quality-Aware Self-Distillation for GUI Grounding.
GUI-RD stands for GUI Reliable Distillation. The checkpoint corresponds to the paper main setting: failed-token gate 0.5, scaling coefficient 3, and teacher top1-probability scaling enabled.
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.
from transformers import AutoModelForMultimodalLM, AutoProcessor
import 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.
@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},
}