metadata
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
pretty_name: Wikipedia
paperswithcode_id: null
license:
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- gfdl
task_categories:
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- fill-mask
task_ids:
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- masked-language-modeling
source_datasets:
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language_bcp47:
- nds-nl
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Dataset Card for Wikipedia
This repo is a fork of the original Hugging Face Wikipedia repo here.
The difference is that this fork does away with the need for apache-beam, and this fork is very fast if you have a lot of CPUs on your machine.
It will use all CPUs available to create a clean Wikipedia pretraining dataset. It takes less than an hour to process all of English wikipedia on a GCP n1-standard-96.
This fork is also used in the OLM Project to pull and process up-to-date wikipedia snapshots.
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://dumps.wikimedia.org
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
Dataset Summary
Wikipedia dataset containing cleaned articles of all languages. The datasets are built from the Wikipedia dump (https://dumps.wikimedia.org/) with one split per language. Each example contains the content of one full Wikipedia article with cleaning to strip markdown and unwanted sections (references, etc.).
The articles are parsed using the mwparserfromhell tool, and we use multiprocess for parallelization.
To load this dataset you need to install these first:
pip install mwparserfromhell==0.6.4 multiprocess==0.70.13
Then, you can load any subset of Wikipedia per language and per date this way:
from datasets import load_dataset
load_dataset("olm/wikipedia", language="en", date="20220920")
You can find the full list of languages and dates here.
Supported Tasks and Leaderboards
The dataset is generally used for Language Modeling.
Languages
You can find the list of languages here.
Dataset Structure
Data Instances
An example looks as follows:
{'id': '1',
'url': 'https://simple.wikipedia.org/wiki/April',
'title': 'April',
'text': 'April is the fourth month...'
}
Data Fields
The data fields are the same among all configurations:
id(str): ID of the article.url(str): URL of the article.title(str): Title of the article.text(str): Text content of the article.
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
Most of Wikipedia's text and many of its images are co-licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License (CC BY-SA) and the GNU Free Documentation License (GFDL) (unversioned, with no invariant sections, front-cover texts, or back-cover texts).
Some text has been imported only under CC BY-SA and CC BY-SA-compatible license and cannot be reused under GFDL; such text will be identified on the page footer, in the page history, or on the discussion page of the article that utilizes the text.
Citation Information
@ONLINE{wikidump,
author = "Wikimedia Foundation",
title = "Wikimedia Downloads",
url = "https://dumps.wikimedia.org"
}