---
license: apache-2.0
task_categories:
- text-generation
language:
- en
- zh
tags:
- language model
pretty_name: Matrix
size_categories:
- n>1T
---

# Matrix

An open-source pretraining dataset containing 4690 billion tokens, this bilingual dataset with both English and Chinese texts is used for training neo models.

## Dataset Composition

The dataset consists of several components, each originating from different sources and serving various purposes in language modeling and processing. Below is a brief overview of each component:

<p>
  <img src="https://cdn-uploads.huggingface.co/production/uploads/654907a4a1faff97850c4eff/1FWMF_t_Mhy0UQmu65Bb1.png" style="float: right; width: 400px; margin-left: 10px;">
  <strong>Common Crawl</strong><br>
  Extracts from the Common Crawl project, featuring a rich diversity of internet text including websites, blogs, news articles, and more.<br>

  <strong>Code</strong><br>
  A collection of coding-related data.<be>

  <strong>Paper</strong><br>
  Consists of academic and research papers covering a broad spectrum of disciplines, offering technical and domain-specific language.<br>

  <strong>Book</strong><br>
  Comprises texts from a range of published books, encompassing literature, non-fiction, textbooks, and more.<br>

  <strong>Instruction</strong><br>
  Features a collection of texts primarily in a Q&A format.<be>

  <strong>Exam</strong><br>
  Contains various educational materials and assessments used in academic examinations.<be>
  
  <strong>News</strong><br>
  A collection of texts from various journalistic sources, reporting on current events and news stories.<br>
  
  <strong>Wiki</strong><br>
  Articles from various encyclopedic sources, not limited to Wikipedia, covering a wide array of topics and information.<br>
  
  <strong>Patent</strong><br>
  Includes texts from patent documents, providing detailed descriptions of inventions and their applications.<br>

</p>

## Citation
```
@article{zhang2024mapneo,
    title   = {MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Series},
    author  = {Ge Zhang and Scott Qu and Jiaheng Liu and Chenchen Zhang and Chenghua Lin and Chou Leuang Yu and Danny Pan and Esther Cheng and Jie Liu and Qunshu Lin and Raven Yuan and Tuney Zheng and Wei Pang and Xinrun Du and Yiming Liang and Yinghao Ma and Yizhi Li and Ziyang Ma and Bill Lin and Emmanouil Benetos and Huan Yang and Junting Zhou and Kaijing Ma and Minghao Liu and Morry Niu and Noah Wang and Quehry Que and Ruibo Liu and Sine Liu and Shawn Guo and Soren Gao and Wangchunshu Zhou and Xinyue Zhang and Yizhi Zhou and Yubo Wang and Yuelin Bai and Yuhan Zhang and Yuxiang Zhang and Zenith Wang and Zhenzhu Yang and Zijian Zhao and Jiajun Zhang and Wanli Ouyang and Wenhao Huang and Wenhu Chen},
    year    = {2024},
    journal = {arXiv preprint arXiv: 2405.19327}
}
```