project_gutenberg

# Project Gutenberg

## Description
[Project Gutenberg](https://www.gutenberg.org) is an online collection of over 75,000 digitized books available as plain text.
We use all books that are 1) English and 2) marked as in the Public Domain according to the provided metadata.
Additionally, we include any books that are part of the [PG19](https://huggingface.co/datasets/deepmind/pg19) dataset, which only includes books that are over 100 years old.
Minimal preprocessing is applied to remove the Project Gutenberg header and footers, but many scanned books include preamble information about who digitized them.

## Dataset Statistics
| Documents | UTF-8 GB |
|-----------|----------|
| 71,810 | 26.2 |

## License Issues
While we aim to produce datasets with completely accurate licensing information, license laundering and inaccurate metadata can cause us to erroneously assign the incorrect license to some documents (for further discussion of this limitation, please see [our paper](https://huggingface.co/papers/2506.05209)). If you believe you have found an instance of incorrect licensing in this dataset, please [start a discussion](https://github.com/r-three/common-pile/discussions/new) on this repository.

## Other Versions
This is the "raw" version of the Project Gutenberg dataset.
If you are looking for the filtered version used to train [Comma v0.1](https://huggingface.co/common-pile/comma-v0.1), you can find it [here](https://huggingface.co/datasets/common-pile/project_gutenberg_filtered).

## Citation
If you use this dataset, please cite:
```bibtex
@article{kandpal2025common,
title={{The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text}},
author={Nikhil Kandpal and Brian Lester and Colin Raffel and Sebastian Majstorovic and Stella Biderman and Baber Abbasi and Luca Soldaini and Enrico Shippole and A. Feder Cooper and Aviya Skowron and Shayne Longpre and Lintang Sutawika and Alon Albalak and Zhenlin Xu and Guilherme Penedo and Loubna Ben and Elie Bakouch and John David and Honglu Fan and Dashiell Stander and Guangyu Song and Aaron Gokaslan and John Kirchenbauer and Tom Goldstein and Brian R and Bhavya Kailkhura and Tyler Murray},
journal={arXiv preprint},
year={2025}
}
```
```bibtex
@article{raecompressive2019,
author = {Rae, Jack W and Potapenko, Anna and Jayakumar, Siddhant M and
Hillier, Chloe and Lillicrap, Timothy P},
title = {Compressive Transformers for Long-Range Sequence Modelling},
journal = {arXiv preprint},
url = {https://arxiv.org/abs/1911.05507},
year = {2019},
}
```

# 古腾堡计划(Project Gutenberg)

## 数据集描述
[古腾堡计划(Project Gutenberg)](https://www.gutenberg.org) 是一个在线馆藏库，收录超过75000部可获取纯文本格式的数字化图书。
我们选用所有满足以下两项条件的图书：1）语言为英语；2）根据所提供的元数据，被标记为属于公有领域（Public Domain）。
此外，我们还纳入了属于[PG19](https://huggingface.co/datasets/deepmind/pg19)数据集的全部图书，该数据集仅收录出版时长超过100年的图书。
本数据集仅执行极简预处理以移除古腾堡计划的页眉与页脚，但部分扫描图书仍保留了关于数字化参与者的前言信息。

## 数据集统计数据
| 文档数量 | UTF-8 总大小（GB） |
|-----------|----------|
| 71,810 | 26.2 |

## 许可相关问题
尽管我们致力于打造许可信息完全准确的数据集，但许可洗白（license laundering）与元数据失准的问题，可能导致我们错误地为部分文档分配了错误的版权许可。如需进一步了解该局限性的相关讨论，请参阅[我们的论文](https://huggingface.co/papers/2506.05209)。
若您发现本数据集存在许可信息标注错误的情况，请前往本仓库[发起讨论](https://github.com/r-three/common-pile/discussions/new)。

## 其他版本
本版本为古腾堡计划数据集的「原始版」。若您需要用于训练[Comma v0.1](https://huggingface.co/common-pile/comma-v0.1)的过滤版数据集，可前往[此处](https://huggingface.co/datasets/common-pile/project_gutenberg_filtered)获取。

## 引用格式
若您使用本数据集，请引用如下文献：
bibtex
@article{kandpal2025common,
title={{The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text}},
author={Nikhil Kandpal and Brian Lester and Colin Raffel and Sebastian Majstorovic and Stella Biderman and Baber Abbasi and Luca Soldaini and Enrico Shippole and A. Feder Cooper and Aviya Skowron and Shayne Longpre and Lintang Sutawika and Alon Albalak and Zhenlin Xu and Guilherme Penedo and Loubna Ben and Elie Bakouch and John David and Honglu Fan and Dashiell Stander and Guangyu Song and Aaron Gokaslan and John Kirchenbauer and Tom Goldstein and Brian R and Bhavya Kailkhura and Tyler Murray},
journal={arXiv preprint},
year={2025}
}

bibtex
@article{raecompressive2019,
author = {Rae, Jack W and Potapenko, Anna and Jayakumar, Siddhant M and
Hillier and Chloe and Lillicrap, Timothy P},
title = {Compressive Transformers for Long-Range Sequence Modelling},
journal = {arXiv preprint},
url = {https://arxiv.org/abs/1911.05507},
year = {2019},
}

搜集汇总

背景与挑战

背景概述

Project Gutenberg数据集是一个包含超过75,000本英文和公共领域数字化书籍的集合，经过最小预处理，占用26.2GB的UTF-8编码空间。数据集可能存在许可证信息不准确的情况，并提供了一个过滤版本用于特定训练目的。