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arXiv:2211.15533cs.CL

The Stack: 3 TB of permissively licensed source code

Denis Kocetkov, Raymond Li, Loubna Ben Allal, Jia Li, Chenghao Mou, Carlos Muñoz Ferrandis, Yacine Jernite, Margaret Mitchell, Sean Hughes, Thomas Wolf, Dzmitry Bahdanau, Leandro von Werra, Harm de Vries

Abstract

Large Language Models (LLMs) play an ever-increasing role in the field of Artificial Intelligence (AI)--not only for natural language processing but also for code understanding and generation. To stimulate open and responsible research on LLMs for code, we introduce The Stack, a 3.1 TB dataset consisting of permissively licensed source code in 30 programming languages. We describe how we collect the full dataset, construct a permissively licensed subset, present a data governance plan, discuss limitations, and show promising results on text2code benchmarks by training 350M-parameter decoders on different Python subsets. We find that (1) near-deduplicating the data significantly boosts performance across all experiments, and (2) it is possible to match previously reported HumanEval and MBPP performance using only permissively licensed data. We make the dataset available at https://hf.co/BigCode, provide a tool called "Am I in The Stack" (https://hf.co/spaces/bigcode/in-the-stack) for developers to search The Stack for copies of their code, and provide a process for code to be removed from the dataset by following the instructions at https://www.bigcode-project.org/docs/about/the-stack/.

arXiv comments
Journal reference
DOI
Subjects
cs.CLComputation and Language cs.AIArtificial Intelligence

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Linked by 3 identifiable commenters in 3 comments across 2 threads, from Mar 2023 to May 2023.

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Discussed in comments2 threads

  1. Replit's new Code LLM: Open Source, 77% smaller than Codex, trained in 1 week 2 comments

    • Oh my bad! I thought I read that, is it based upon: https://arxiv.org/abs/2211.15533 (The Stack) ?

      GreedClarifiesView on HNParent context

    • You can view the prompts, solutions, and checks here[0]. See my sibling comment (to yours) where I quote the Human Eval paper and do some more analysis. But I think if you look at [0] you'll see that these aren't really unique problems and are likely to have large repetitions in…

      godelskiView on HNParent context

  2. Launch HN: CodeComplete (YC W23) – Copilot for Enterprise 1 comment

    • Congrats on the launch. I think you should share some technical details for a more substantial pitch. You are using the OSS BigCode effort and "The Stack" [1, 2] (as you say in another comment), which is great. A few questions that might help an enterprise customer: How big is…

      saurabh20nView on HNParent context

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