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**BlenderLLM** is built using **Qwen2.5-Coder-7B-Instruct** as the base model. It has been fine-tuned on the **BlendNet** training dataset and further optimized through **Self-improvement** techniques to achieve the best performance.
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For more details, please visit our [GitHub repository](https://github.com/FreedomIntelligence/BlenderLLM)
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**BlenderLLM** is built using **Qwen2.5-Coder-7B-Instruct** as the base model. It has been fine-tuned on the **BlendNet** training dataset and further optimized through **Self-improvement** techniques to achieve the best performance.
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For more details, please visit our [GitHub repository](https://github.com/FreedomIntelligence/BlenderLLM) or refer to our [arXiv paper](https://www.arxiv.org/abs/2412.14203).
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## 📖 Citation
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```angular2
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@misc{du2024blenderllmtraininglargelanguage,
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title={BlenderLLM: Training Large Language Models for Computer-Aided Design with Self-improvement},
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author={Yuhao Du and Shunian Chen and Wenbo Zan and Peizhao Li and Mingxuan Wang and Dingjie Song and Bo Li and Yan Hu and Benyou Wang},
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year={2024},
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eprint={2412.14203},
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archivePrefix={arXiv},
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primaryClass={cs.HC},
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url={https://arxiv.org/abs/2412.14203},
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}
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```
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We are from the School of Data Science (SDS), the Chinese University of Hong Kong, Shenzhen (CUHKSZ).
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