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GitHub - PootieT/MultiPL-E: A multi-programming language benchmark for evaluating the performance of large language model of code.
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A multi-programming language benchmark for evaluating the performance of large language model of code.

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Multi-Programming Language Evaluation of Large Language Models of Code (MultiPL-E)

MultiPL-E is a system for translating unit test-driven neural code generation benchmarks to new languages. We have used MultiPL-E to translate two popular Python benchmarks (HumanEval and MBPP) to 18 other programming languages.

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  • Version 0.3.0 (work in progress)

  • Version 0.2.0: used to evaluate SantaCoder

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A multi-programming language benchmark for evaluating the performance of large language model of code.

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  • Python 86.5%
  • Lua 10.3%
  • Jupyter Notebook 2.1%
  • Shell 0.9%
  • Dockerfile 0.2%
  • C++ 0.0%