Datasets:
Tasks:
Text Generation
Modalities:
Text
Sub-tasks:
language-modeling
Languages:
English
Size:
100K - 1M
License:
Merge branch 'main' of https://huggingface.co/datasets/hoskinson-center/proof-pile into main
Browse files
README.md
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- language-modeling
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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
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- ArXiv.math (
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- Open-source math textbooks (50MB)
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- Formal mathematics libraries (500MB)
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- Lean mathlib and other Lean repositories
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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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#
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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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## Contributions
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Authors: Zhangir Azerbayev, Edward Ayers, Bartosz Piotrowski.
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We would like to thank Jeremy Avigad for
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- language-modeling
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# Dataset Description
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The `proof-pile` is a 40GB 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 (37GB)
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- Open-source math textbooks (50MB)
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- Formal mathematics libraries (500MB)
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- Lean mathlib and other Lean repositories
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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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# Configurations
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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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# Evaluation
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The version of `set.mm` in this dataset has 10% of proofs replaced with the `?` character in order to preserve a validation and test set for Metamath provers pre-trained on the `proof-pile`. The precise split can be found here: [validation](https://github.com/zhangir-azerbayev/mm-extract/blob/main/valid_decls.json) and [test](https://github.com/zhangir-azerbayev/mm-extract/blob/main/test_decls.json).
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The Lean mathlib commit used in this dataset is `6313863`. Theorems created in subsequent commits can be used for evaluating Lean theorem provers.
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This dataset contains only the training set of the [MATH dataset](https://github.com/hendrycks/math). However, because this dataset contains ProofWiki, the Stacks Project, Trench's Analysis, and Stein's Number Theory, models trained on it cannot be evaluated on the [NaturalProofs dataset](https://github.com/wellecks/naturalproofs).
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## Contributions
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Authors: Zhangir Azerbayev, Edward Ayers, Bartosz Piotrowski.
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We would like to thank Jeremy Avigad, Albert Jiang, and Wenda Li for their invaluable guidance, and the Hoskinson Center for Formal Mathematics for its support.
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