Instructions to use microsoft/GUI-Actor-Verifier-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use microsoft/GUI-Actor-Verifier-2B with Transformers:

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

pipe = pipeline("image-text-to-text", model="microsoft/GUI-Actor-Verifier-2B")
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("microsoft/GUI-Actor-Verifier-2B")
model = AutoModelForImageTextToText.from_pretrained("microsoft/GUI-Actor-Verifier-2B")
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

vLLM

How to use microsoft/GUI-Actor-Verifier-2B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "microsoft/GUI-Actor-Verifier-2B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "microsoft/GUI-Actor-Verifier-2B",
		"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/microsoft/GUI-Actor-Verifier-2B

SGLang

How to use microsoft/GUI-Actor-Verifier-2B 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 "microsoft/GUI-Actor-Verifier-2B" \
    --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": "microsoft/GUI-Actor-Verifier-2B",
		"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 "microsoft/GUI-Actor-Verifier-2B" \
        --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": "microsoft/GUI-Actor-Verifier-2B",
		"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 microsoft/GUI-Actor-Verifier-2B with Docker Model Runner:
```
docker model run hf.co/microsoft/GUI-Actor-Verifier-2B
```

qianhuiwu commited on Jun 4, 2025

Commit

cc3ad83

verified ·

1 Parent(s): c8a234a

update paper link.

Browse files

Files changed (1) hide show

README.md +3 -3

README.md CHANGED Viewed

@@ -13,7 +13,7 @@ This model was introduced in the paper [**GUI-Actor: Coordinate-Free Visual Grou
 It is developed based on [UI-TARS-2B-SFT](https://huggingface.co/ByteDance-Seed/UI-TARS-2B-SFT) and is designed to predict the correctness of an action position given a language instruction. This model is well-suited for **GUI-Actor**, as its attention map effectively provides diverse candidates for verification with only a single inference.
-For more details on model design and evaluation, please check: [🏠 Project Page](https://aka.ms/GUI-Actor) | [💻 Github Repo](https://github.com/microsoft/GUI-Actor) | [📑 Paper]().
 | Model List                                  | Hugging Face Link                         |
@@ -194,9 +194,9 @@ answer = ground_only_positive(model, tokenizer, processor, instruction, image, p
     title={GUI-Actor: Coordinate-Free Visual Grounding for GUI Agents},
     author={Qianhui Wu and Kanzhi Cheng and Rui Yang and Chaoyun Zhang and Jianwei Yang and Huiqiang Jiang and Jian Mu and Baolin Peng and Bo Qiao and Reuben Tan and Si Qin and Lars Liden and Qingwei Lin and Huan Zhang and Tong Zhang and Jianbing Zhang and Dongmei Zhang and Jianfeng Gao},
     year={2025},
-    eprint={},
     archivePrefix={arXiv},
     primaryClass={cs.CV},
-    url={},
 }
 ```

 It is developed based on [UI-TARS-2B-SFT](https://huggingface.co/ByteDance-Seed/UI-TARS-2B-SFT) and is designed to predict the correctness of an action position given a language instruction. This model is well-suited for **GUI-Actor**, as its attention map effectively provides diverse candidates for verification with only a single inference.
+For more details on model design and evaluation, please check: [🏠 Project Page](https://aka.ms/GUI-Actor) | [💻 Github Repo](https://github.com/microsoft/GUI-Actor) | [📑 Paper](https://www.arxiv.org/pdf/2506.03143).
 | Model List                                  | Hugging Face Link                         |
     title={GUI-Actor: Coordinate-Free Visual Grounding for GUI Agents},
     author={Qianhui Wu and Kanzhi Cheng and Rui Yang and Chaoyun Zhang and Jianwei Yang and Huiqiang Jiang and Jian Mu and Baolin Peng and Bo Qiao and Reuben Tan and Si Qin and Lars Liden and Qingwei Lin and Huan Zhang and Tong Zhang and Jianbing Zhang and Dongmei Zhang and Jianfeng Gao},
     year={2025},
+    eprint={2506.03143},
     archivePrefix={arXiv},
     primaryClass={cs.CV},
+    url={https://www.arxiv.org/pdf/2506.03143},
 }
 ```