Evaluating Large Language Models Trained on Code
human evaluators. To accurately benchmark our model, we create a dataset of 164 original programming problems with unit tests. These problems assess language compre-hension, algorithms, and simple mathematics, with some comparable to simple software interview questions. We release this data along with an evaluation framework at
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