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Evaluating Large Language Models Trained on Code

arxiv.org

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Re: Evaluating Large Language Models Trained on Code

#2
> On HumanEval, a new evaluation set we release to measure functional correctness for synthesizing programs from docstrings, our model solves 28.8% of the problems, while GPT-3 solves 0% and GPT-J solves 11.4%.

Interesting that they are comparing their model with GPT-J.