Datasets:
language:
- en pretty_name: 'TokenMonster Datasets: English, Code, Fiction, Non-fiction' size_categories:
- 1B<n<10B tags:
- text
- english
- fiction
- nonfiction
- non-fiction
- code
- code samples
- tokenization
- tokenization datasets
- datasets task_categories:
- text-generation
TokenMonster Datasets: English, Code, Fiction, Non-fiction
Included are datasets that were used to generate the TokenMonster pre-built vocabularies.
The training data mostly came from Red Pajamas 1B Token Sample. However, to reduce formal English and emphasize other languages, informal writing and code, c4_sample & cc_sample were cropped to 100MB, and Reddit conversations data were added (also cropped to 100MB.)
Additionally, equally weighted code samples of 2MB per language (code_2mb) and 10MB per language (code_10mb) were added for 30 different programming languages to ensure all programming languages have representation. The source of the code samples was codeparrot/github-code. To ensure a range of coding styles, I allowed only 1 file per GitHub repository, and per file a maximum of 200 lines selected from the middle of the file.
Given the evolving nature of writing styles, I felt that book_sample.txt, which consists of out-of-copyright books, was not a good representation of contemporary fiction. To better represent a more modern style, I curated fiction.txt and fiction_100mb.txt by throwing together a few other datasets and cleaning it up.
| Filename | Filesize |
|---|---|
| arxiv_sample.txt | 88,925,569 |
| book_sample.txt | 108,069,616 |
| c4_sample.txt | 100,560,318 |
| cc_2023-06_sample.txt | 100,852,231 |
| code_2mb.txt | 62,895,904 |
| code_10mb.txt | 314,006,799 |
| fiction.txt | 357,119,086 |
| fiction_100mb.txt | 94,235,489 |
| github_sample.txt | 191,123,094 |
| stackexchange_sample.txt | 71,940,138 |
| wikipedia_sample.txt | 79,181,873 |
| reddit.txt | 100,027,565 |
Note: fiction_100mb.txt is a subset of fiction.txt, and code_2mb.txt is a subset of code_10mb.txt.