Image-Text-to-Text
Transformers
Safetensors
English
Chinese
qwen2_vl
multimodal
gui
conversational
text-generation-inference
Instructions to use OpenGVLab/ZeroGUI-OSWorld-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/ZeroGUI-OSWorld-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="OpenGVLab/ZeroGUI-OSWorld-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("OpenGVLab/ZeroGUI-OSWorld-7B") model = AutoModelForImageTextToText.from_pretrained("OpenGVLab/ZeroGUI-OSWorld-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
- vLLM
How to use OpenGVLab/ZeroGUI-OSWorld-7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpenGVLab/ZeroGUI-OSWorld-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": "OpenGVLab/ZeroGUI-OSWorld-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/OpenGVLab/ZeroGUI-OSWorld-7B
- SGLang
How to use OpenGVLab/ZeroGUI-OSWorld-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 "OpenGVLab/ZeroGUI-OSWorld-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": "OpenGVLab/ZeroGUI-OSWorld-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 "OpenGVLab/ZeroGUI-OSWorld-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": "OpenGVLab/ZeroGUI-OSWorld-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 OpenGVLab/ZeroGUI-OSWorld-7B with Docker Model Runner:
docker model run hf.co/OpenGVLab/ZeroGUI-OSWorld-7B
Update README.md
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@@ -41,6 +41,7 @@ If you find this work helpful in your research, please consider citing:
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@article{yang2025zerogui,
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title={ZeroGUI: Automating Online GUI Learning at Zero Human Cost},
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author={Yang, Chenyu and Shiqian, Su and Liu, Shi and Dong, Xuan and Yu, Yue and Su, Weijie and Wang, Xuehui and Liu, Zhaoyang and Zhu, Jinguo and Li, Hao and Wang, Wenhai and Qiao, Yu and Zhu, Xizhou and Dai, Jifeng},
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year={2025}
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}
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```
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@article{yang2025zerogui,
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title={ZeroGUI: Automating Online GUI Learning at Zero Human Cost},
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author={Yang, Chenyu and Shiqian, Su and Liu, Shi and Dong, Xuan and Yu, Yue and Su, Weijie and Wang, Xuehui and Liu, Zhaoyang and Zhu, Jinguo and Li, Hao and Wang, Wenhai and Qiao, Yu and Zhu, Xizhou and Dai, Jifeng},
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journal={arXiv preprint arXiv:2505.23762},
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year={2025}
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}
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```
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