Instructions to use afx-team/UI-UG-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use afx-team/UI-UG-7B with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="afx-team/UI-UG-7B")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("afx-team/UI-UG-7B")
model = AutoModelForImageTextToText.from_pretrained("afx-team/UI-UG-7B")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use afx-team/UI-UG-7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "afx-team/UI-UG-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "afx-team/UI-UG-7B",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/afx-team/UI-UG-7B

SGLang

How to use afx-team/UI-UG-7B with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "afx-team/UI-UG-7B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "afx-team/UI-UG-7B",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "afx-team/UI-UG-7B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "afx-team/UI-UG-7B",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use afx-team/UI-UG-7B with Docker Model Runner:
```
docker model run hf.co/afx-team/UI-UG-7B
```

airbobby commited on Sep 30, 2025

Commit

6418137

verified ·

1 Parent(s): 7a3826c

Update README.md

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Files changed (1) hide show

README.md +19 -2

README.md CHANGED Viewed

@@ -8,7 +8,7 @@ tags:
 - UI
 - UI-UG
 - MLLM
-# - arxiv:2509.0000
 ---
@@ -19,10 +19,11 @@ tags:
 [![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/)
 [![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://www.apache.org/licenses/LICENSE-2.0)
 [![Hugging Face Model](https://img.shields.io/badge/🤗%20Hugging%20Face-Model-yellow.svg)](https://huggingface.co/neovateai/UI-UG-7B)
 [![GitHub Repository](https://img.shields.io/badge/GitHub-Repository-181717.svg?logo=github)](https://github.com/neovateai/UI-UG)
-[**🤗 Model**](https://huggingface.co/neovateai/UI-UG-7B) | [**🚀 Quick Start**](#-quick-start) | [**📊 Evaluation**](#-evaluation) | [**📄 License**](#-license) | [📖 Paper](Coming Soon)
 </div>
@@ -236,6 +237,22 @@ This project is licensed under the [Apache 2.0 License](https://www.apache.org/l
 - [**VLLM**](https://github.com/vllm-project/vllm) - High-performance inference framework
 - [**Ant Group**](https://www.antgroup.com) & [**AFX Team**](https://afx-team.github.io) - Technical support and scenario applications
 ---
 <div align="center">

 - UI
 - UI-UG
 - MLLM
+- arxiv:2509.24361
 ---
 [![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/)
 [![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://www.apache.org/licenses/LICENSE-2.0)
+[![Paper](https://img.shields.io/badge/paper-arxiv-red.svg)](https://arxiv.org/abs/2509.24361)
 [![Hugging Face Model](https://img.shields.io/badge/🤗%20Hugging%20Face-Model-yellow.svg)](https://huggingface.co/neovateai/UI-UG-7B)
 [![GitHub Repository](https://img.shields.io/badge/GitHub-Repository-181717.svg?logo=github)](https://github.com/neovateai/UI-UG)
+[**📖 Paper**](https://arxiv.org/abs/2509.24361) | [**🤗 Model**](https://huggingface.co/neovateai/UI-UG-7B) | [**🚀 Quick Start**](#-quick-start) | [**📊 Evaluation**](#-evaluation) | [**📄 License**](#-license)
 </div>
 - [**VLLM**](https://github.com/vllm-project/vllm) - High-performance inference framework
 - [**Ant Group**](https://www.antgroup.com) & [**AFX Team**](https://afx-team.github.io) - Technical support and scenario applications
+## 📖 Citation
+If you find this work useful, please consider citing:
+```bibtex
+@misc{yang2025uiugunifiedmllmui,
+      title={UI-UG: A Unified MLLM for UI Understanding and Generation},
+      author={Hao Yang and Weijie Qiu and Ru Zhang and Zhou Fang and Ruichao Mao and Xiaoyu Lin and Maji Huang and Zhaosong Huang and Teng Guo and Shuoyang Liu and Hai Rao},
+      year={2025},
+      eprint={2509.24361},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2509.24361},
+}
+```
 ---
 <div align="center">