The Heap: A Contamination-Free Multilingual Code Dataset for Evaluating Large Language Models

TL;DR

The paper introduces The Heap, a large, multilingual, deduplicated code dataset designed to enable fair evaluation of large language models without data contamination.

Contribution

It provides a comprehensive, multilingual, deduplicated code dataset that facilitates unbiased evaluation of large language models across 57 programming languages.

Findings

Contains 57 programming languages

Deduplicated with respect to other datasets

Enables contamination-free evaluation

Abstract

The recent rise in the popularity of large language models has spurred the development of extensive code datasets needed to train them. This has left limited code available for collection and use in the downstream investigation of specific behaviors, or evaluation of large language models without suffering from data contamination. To address this problem, we release The Heap, a large multilingual dataset covering 57 programming languages that has been deduplicated with respect to other open datasets of code, enabling researchers to conduct fair evaluations of large language models without significant data cleaning overhead.