Merge branch 'main' of https://huggingface.co/datasets/hoskinson-center/proof-pile into main

README.md

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+---
+annotations_creators:
+- no-annotation
+language:
+- en
+language_creators:
+- found
+license: []
+multilinguality:
+- monolingual
+pretty_name: proof-pile
+size_categories: []
+source_datasets: []
+tags:
+- math
+- mathematics
+- formal-mathematics
+task_categories:
+- text-generation
+task_ids:
+- language-modeling
+---
+
+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. 
+# Dataset Card for Proof-pile
+
+# Dataset Description
+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
+- ArXiv.math (40GB)
+- Open-source math textbooks (50MB)
+- Formal mathematics libraries (500MB)
+    - Lean mathlib and other Lean repositories 
+    - Isabelle AFP
+    - Coq mathematical components and other Coq repositories 
+    - HOL Light
+    - set.mm
+    - Mizar Mathematical Library
+- Math Overflow and Math Stack Exchange (500MB)
+- Wiki-style sources (50MB)
+  - ProofWiki
+  - Wikipedia math articles
+- MATH dataset (6MB)
+
+# Supported Tasks
+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. 
+
+# Languages
+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.
+
+ # Splits 
+ 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. 
+ 
+ Note that in the `"stack-exchange"`, `"wiki"`, and `"stack-exchange"` configurations, multiple documents are included in them same instance separated by the string `"<|endoftext|>"`. 
+
+## Contributions
+Authors: Zhangir Azerbayev, Edward Ayers, Bartosz Piotrowski. 
+
+We would like to thank Jeremy Avigad for his invaluable perspective and guidance, and the Hoskinson Center for Formal Mathematics for its support.