Image-Text-to-Text
Transformers
Safetensors
English
gamescaling
game-agent
embodied-agent
keyboard-mouse
continued-pretraining
qwen3_5
Instructions to use THUSI-Lab/GameScaling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use THUSI-Lab/GameScaling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="THUSI-Lab/GameScaling")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("THUSI-Lab/GameScaling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use THUSI-Lab/GameScaling with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "THUSI-Lab/GameScaling" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "THUSI-Lab/GameScaling", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/THUSI-Lab/GameScaling
- SGLang
How to use THUSI-Lab/GameScaling 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 "THUSI-Lab/GameScaling" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "THUSI-Lab/GameScaling", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "THUSI-Lab/GameScaling" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "THUSI-Lab/GameScaling", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use THUSI-Lab/GameScaling with Docker Model Runner:
docker model run hf.co/THUSI-Lab/GameScaling
Card: research-only licence; Code badge -> GitHub
Browse files
README.md
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<p align="center">
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<a href="https://gamescaling.github.io" style="display:inline-block;margin:2px;"><img src="https://img.shields.io/badge/Project-Page-1f6feb?style=for-the-badge&logo=googlechrome&logoColor=white" alt="Project Page" style="display:inline-block;vertical-align:middle;margin:0;"></a>
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<a href="https://gamescaling.github.io" style="display:inline-block;margin:2px;"><img src="https://img.shields.io/badge/arXiv-coming%20soon-lightgrey?style=for-the-badge&logo=arxiv&logoColor=white" alt="arXiv (coming soon)" style="display:inline-block;vertical-align:middle;margin:0;"></a>
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<a href="https://
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<a href="https://huggingface.co/THUSI-Lab/GameScaling" style="display:inline-block;margin:2px;"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Models-THUSI--Lab%2FGameScaling-ffcc4d?style=for-the-badge" alt="Models" style="display:inline-block;vertical-align:middle;margin:0;"></a>
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<a href="https://www.apache.org/licenses/LICENSE-2.0" style="display:inline-block;margin:2px;"><img src="https://img.shields.io/badge/License-Apache%202.0-2ea44f?style=for-the-badge" alt="License: Apache 2.0" style="display:inline-block;vertical-align:middle;margin:0;"></a>
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</p>
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## License
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## Citation
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<p align="center">
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<a href="https://gamescaling.github.io" style="display:inline-block;margin:2px;"><img src="https://img.shields.io/badge/Project-Page-1f6feb?style=for-the-badge&logo=googlechrome&logoColor=white" alt="Project Page" style="display:inline-block;vertical-align:middle;margin:0;"></a>
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<a href="https://gamescaling.github.io" style="display:inline-block;margin:2px;"><img src="https://img.shields.io/badge/arXiv-coming%20soon-lightgrey?style=for-the-badge&logo=arxiv&logoColor=white" alt="arXiv (coming soon)" style="display:inline-block;vertical-align:middle;margin:0;"></a>
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<a href="https://github.com/THUSI-Lab/GameScaling" style="display:inline-block;margin:2px;"><img src="https://img.shields.io/badge/Code-GitHub-181717?style=for-the-badge&logo=github&logoColor=white" alt="Code" style="display:inline-block;vertical-align:middle;margin:0;"></a>
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<a href="https://huggingface.co/THUSI-Lab/GameScaling" style="display:inline-block;margin:2px;"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Models-THUSI--Lab%2FGameScaling-ffcc4d?style=for-the-badge" alt="Models" style="display:inline-block;vertical-align:middle;margin:0;"></a>
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<a href="https://www.apache.org/licenses/LICENSE-2.0" style="display:inline-block;margin:2px;"><img src="https://img.shields.io/badge/License-Apache%202.0-2ea44f?style=for-the-badge" alt="License: Apache 2.0" style="display:inline-block;vertical-align:middle;margin:0;"></a>
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</p>
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## License
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GameScaling is a **purely scientific research** project. We carry out **no commercial activity** of
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any kind with it: nothing here is sold, licensed for a fee, or used in any product or service.
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- **Models and code: Apache-2.0.** The weights and the inference code are released under the
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[Apache License 2.0](LICENSE). The models are continued pre-trained from
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[Qwen3.5](https://huggingface.co/Qwen/Qwen3.5-9B), which is also Apache 2.0.
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- **Gameplay data is not released.** The training corpus stays private; game frames in this
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repository (e.g. `examples/doom_battle1.jpg`) only illustrate how to use the model.
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- **Game copyright belongs to the publishers.** All game titles, footage, copyrights, trademarks and
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other game assets referenced here belong to their respective publishers and owners. The Apache
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2.0 licence covers our weights and code only and grants no right to any game content.
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## Citation
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