Datasets:
Tasks:
Text Generation
Modalities:
Text
Sub-tasks:
language-modeling
Languages:
English
Size:
100K - 1M
License:
zhangirazerbayev
commited on
Commit
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README.md
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Note: this repo is a WIP and does not yet implement all features described below. It is certainly not ready to be used to train a model.
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# Dataset
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The `proof-pile` is a 45GB pre-training dataset of mathematical text. The dataset is composed of diverse sources of both informal and formal mathematics, namely
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- ArXiv.math (40GB)
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- Open-source math textbooks (50MB)
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- ProofWiki
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- Wikipedia math articles
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- MATH dataset (6MB)
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Note: this repo is a WIP and does not yet implement all features described below. It is certainly not ready to be used to train a model.
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# Dataset Card for Proof-pile
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# Dataset Description
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The `proof-pile` is a 45GB pre-training dataset of mathematical text. The dataset is composed of diverse sources of both informal and formal mathematics, namely
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- ArXiv.math (40GB)
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- Open-source math textbooks (50MB)
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- ProofWiki
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- Wikipedia math articles
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- MATH dataset (6MB)
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# Supported Tasks
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This dataset is intended to be used for pre-training language models. We envision models pre-trained on the `proof-pile` will have many downstream applications, including informal quantitative reasoning, formal theorem proving, semantic search for formal mathematics, and autoformalization.
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# Languages
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All informal mathematics in the `proof-pile` is written in English and LaTeX (arXiv articles in other languages are filtered out using [languagedetect](https://github.com/shuyo/language-detection/blob/wiki/ProjectHome.md)). Formal theorem proving languages represented in this dataset are Lean 3, Isabelle, Coq, HOL Light, Metamath, and Mizar.
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# Splits
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The data is sorted into `"arxiv", "books", "formal", "stack-exchange", "wiki",` and `"math-dataset"` configurations. This is so that it is easy to upsample particular configurations during pre-training with the `datasets.interleave_datasets()` function.
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