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  • Ziyang Luo, Can Xu, Pu Zhao
    |
    Jun 14th, 2023
    |
    preprint
    Ziyang Luo, Can Xu, Pu Zhao
    Jun 14th, 2023

    Code Large Language Models (Code LLMs), such as StarCoder, have demonstrated exceptional performance in code-related tasks. However, most existing models are solely pre-trained on extensive raw code data without instruction fine-tuning. In this paper, we introduce WizardCoder, which empowers Code LLMs with complex instruction fine-tuning, by adapting the Evol-Instruct method to the domain of code. Through comprehensive experiments on four prominent code generation benchmarks, namely...

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