raw_v.01_parquet

# Common Pile v0.1 — Parquet Consolidated

## Description
This dataset bundles **all “raw” corpora from the Common Pile v0.1 Raw Data [collection](https://huggingface.co/collections/common-pile/common-pile-v01-raw-data-6826b454a5a6a445d0b51b37)**, converted to Apache Parquet and consolidated in a single repository.

Nothing has been filtered or modified; the only changes are:
* **Format:** original JSON → Parquet
* **Layout:** many repositories → one consolidated dataset
* **Extra column:** a `len_category` bucket for quick length-based filtering

Only the three original columns (`id`, `text`, `source`) are carried over; `len_category` is derived from `text` length.

## Dataset Schema

| Column | Type | Notes |
|--------|--------|---------------------------------------------------------------|
| `id` | string | Original document ID |
| `text` | string | UTF-8 plain text |
| `source` | string | Name of the originating corpus (e.g. `library_of_congress`) |
| `len_category` | string | Bucketed document length (bytes)|

## License Issues
Licensing follows the individual corpora.

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
* [Per-corpus “raw” datasets](https://huggingface.co/collections/common-pile/common-pile-v01-raw-data-6826b454a5a6a445d0b51b37)
* [Filtered set used for Comma v0.1 training](https://huggingface.co/datasets/common-pile/common-pile-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}
}

# Common Pile v0.1 — 合并式Parquet格式数据集

## 描述
本数据集整合了**通用语料库（Common Pile）v0.1原始数据合集**中的全部“原始”语料，相关原始数据合集可参阅 [链接](https://huggingface.co/collections/common-pile/common-pile-v01-raw-data-6826b454a5a6a445d0b51b37)，并将其转换为Apache Parquet格式后合并至单个代码仓库中。

本数据集未经过任何过滤或修改，仅做了以下三处调整：
* **格式转换**：将原始JSON格式转换为Apache Parquet格式
* **布局整合**：将多个分散的代码仓库合并为单个数据集
* **新增列**：新增`len_category`长度分桶列，用于快速基于文本长度进行筛选

仅保留原始的三列字段（`id`、`text`、`source`）；`len_category`列根据`text`的长度计算得到。

## 数据集模式
| 列名 | 数据类型 | 说明 |
|--------|--------|---------------------------------------------------------------|
| `id` | 字符串 | 原始文档ID |
| `text` | 字符串 | UTF-8编码纯文本 |
| `source` | 字符串 | 来源语料库名称（例如`library_of_congress`） |
| `len_category` | 字符串 | 按字节数分桶后的文档长度 |

## 授权说明
本数据集的授权遵循各原始语料库的授权协议。
尽管我们致力于提供完全准确的授权信息，但由于“授权洗白（license laundering）”及元数据不准确等问题，可能会导致我们错误地为部分文档分配了错误的授权协议（关于该局限性的详细讨论，请参阅 [我们的论文](https://huggingface.co/papers/2506.05209)）。若您发现本数据集存在授权信息错误的情况，请前往本代码仓库 [发起讨论](https://github.com/r-three/common-pile/discussions/new)。

## 其他版本
* [单语料库“原始”数据集合集](https://huggingface.co/collections/common-pile/common-pile-v01-raw-data-6826b454a5a6a445d0b51b37)
* [用于Comma v0.1训练的过滤版数据集](https://huggingface.co/datasets/common-pile/common-pile-filtered)

## 引用方式
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}
}