README.md

metadata

annotations_creators:
  - no-annotation
language_creators:
  - crowdsourced
pretty_name: Wikipedia
paperswithcode_id: null
license:
  - cc-by-sa-3.0
  - gfdl
task_categories:
  - text-generation
  - fill-mask
task_ids:
  - language-modeling
  - masked-language-modeling
source_datasets:
  - original
multilinguality:
  - multilingual
size_categories:
  - n<1K
  - 1K<n<10K
  - 10K<n<100K
  - 100K<n<1M
  - 1M<n<10M
language:
  - ab
  - ace
  - ady
  - af
  - ak
  - als
  - alt
  - am
  - ami
  - an
  - ang
  - anp
  - ar
  - arc
  - ary
  - arz
  - as
  - ast
  - atj
  - av
  - avk
  - awa
  - ay
  - az
  - azb
  - ba
  - ban
  - bar
  - bcl
  - be
  - bg
  - bh
  - bi
  - bjn
  - blk
  - bm
  - bn
  - bo
  - bpy
  - br
  - bs
  - bug
  - bxr
  - ca
  - cdo
  - ce
  - ceb
  - ch
  - cho
  - chr
  - chy
  - ckb
  - co
  - cr
  - crh
  - cs
  - csb
  - cu
  - cv
  - cy
  - da
  - dag
  - de
  - din
  - diq
  - dsb
  - dty
  - dv
  - dz
  - ee
  - el
  - eml
  - eo
  - es
  - et
  - eu
  - ext
  - fa
  - fat
  - ff
  - fi
  - fj
  - fo
  - fr
  - frp
  - frr
  - fur
  - fy
  - ga
  - gag
  - gan
  - gcr
  - gd
  - gl
  - glk
  - gn
  - gom
  - gor
  - got
  - gu
  - guc
  - gur
  - guw
  - gv
  - ha
  - hak
  - haw
  - he
  - hi
  - hif
  - ho
  - hr
  - hsb
  - ht
  - hu
  - hy
  - hyw
  - ia
  - id
  - ie
  - ig
  - ii
  - ik
  - ilo
  - inh
  - io
  - is
  - it
  - iu
  - ja
  - jam
  - jbo
  - jv
  - ka
  - kaa
  - kab
  - kbd
  - kbp
  - kcg
  - kg
  - ki
  - kj
  - kk
  - kl
  - km
  - kn
  - ko
  - koi
  - krc
  - ks
  - ksh
  - ku
  - kv
  - kw
  - ky
  - la
  - lad
  - lb
  - lbe
  - lez
  - lfn
  - lg
  - li
  - lij
  - lld
  - lmo
  - ln
  - lo
  - lrc
  - lt
  - ltg
  - lv
  - mad
  - mai
  - mdf
  - mg
  - mh
  - mhr
  - mi
  - min
  - mk
  - ml
  - mn
  - mni
  - mnw
  - mr
  - mrj
  - ms
  - mt
  - mus
  - mwl
  - my
  - myv
  - mzn
  - nah
  - nap
  - nds
  - ne
  - new
  - ng
  - nia
  - nl
  - nn
  - 'no'
  - nov
  - nqo
  - nrm
  - nso
  - nv
  - ny
  - oc
  - olo
  - om
  - or
  - os
  - pa
  - pag
  - pam
  - pap
  - pcd
  - pcm
  - pdc
  - pfl
  - pi
  - pih
  - pl
  - pms
  - pnb
  - pnt
  - ps
  - pt
  - pwn
  - qu
  - rm
  - rmy
  - rn
  - ro
  - ru
  - rue
  - rw
  - sa
  - sah
  - sat
  - sc
  - scn
  - sco
  - sd
  - se
  - sg
  - sh
  - shi
  - shn
  - si
  - sk
  - skr
  - sl
  - sm
  - smn
  - sn
  - so
  - sq
  - sr
  - srn
  - ss
  - st
  - stq
  - su
  - sv
  - sw
  - szl
  - szy
  - ta
  - tay
  - tcy
  - te
  - tet
  - tg
  - th
  - ti
  - tk
  - tl
  - tn
  - to
  - tpi
  - tr
  - trv
  - ts
  - tt
  - tum
  - tw
  - ty
  - tyv
  - udm
  - ug
  - uk
  - ur
  - uz
  - ve
  - vec
  - vep
  - vi
  - vls
  - vo
  - wa
  - war
  - wo
  - wuu
  - xal
  - xh
  - xmf
  - yi
  - yo
  - za
  - zea
  - zh
  - zu
language_bcp47:
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  - be-x-old
  - cbk-zam
  - fiu-vro
  - map-bms
  - nds-nl
  - roa-rup
  - roa-tara
  - simple
  - zh-classical
  - zh-min-nan
  - zh-yue
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      - name: url
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      - name: title
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      - name: text
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  - config_name: 20230601.vi
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      - name: text
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  - config_name: 20230601.vls
    features:
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        dtype: string
      - name: title
        dtype: string
      - name: text
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    splits:
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    dataset_size: 11296047
  - config_name: 20230601.vo
    features:
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      - name: title
        dtype: string
      - name: text
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    splits:
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    dataset_size: 18943004
  - config_name: 20230601.wa
    features:
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      - name: title
        dtype: string
      - name: text
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    splits:
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    dataset_size: 11990482
  - config_name: 20230601.war
    features:
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        dtype: string
      - name: url
        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
    splits:
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    download_size: 109807953
    dataset_size: 468715357
  - config_name: 20230601.wo
    features:
      - name: id
        dtype: string
      - name: url
        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
    splits:
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        num_examples: 1719
    download_size: 2076485
    dataset_size: 3498671
  - config_name: 20230601.wuu
    features:
      - name: id
        dtype: string
      - name: url
        dtype: string
      - name: title
        dtype: string
      - name: text
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    splits:
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    dataset_size: 24986530
  - config_name: 20230601.xal
    features:
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        dtype: string
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    splits:
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    download_size: 508481
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  - config_name: 20230601.xh
    features:
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        dtype: string
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        dtype: string
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        dtype: string
    splits:
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    dataset_size: 2320277
  - config_name: 20230601.xmf
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        dtype: string
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    splits:
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    dataset_size: 36557690
  - config_name: 20230601.yi
    features:
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    splits:
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    dataset_size: 36031133
  - config_name: 20230601.yo
    features:
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      - name: title
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        num_examples: 33179
    download_size: 8274108
    dataset_size: 18018480
  - config_name: 20230601.za
    features:
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        num_examples: 2722
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    dataset_size: 1276590
  - config_name: 20230601.zea
    features:
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    splits:
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        num_examples: 5756
    download_size: 2547904
    dataset_size: 5059421
  - config_name: 20230601.zh
    features:
      - name: id
        dtype: string
      - name: url
        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
    splits:
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        num_bytes: 2720688196
        num_examples: 1357881
    download_size: 1718953037
    dataset_size: 2720688196
  - config_name: 20230601.zh-classical
    features:
      - name: id
        dtype: string
      - name: url
        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
    splits:
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        num_examples: 12513
    download_size: 9882532
    dataset_size: 14617535
  - config_name: 20230601.zh-min-nan
    features:
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        dtype: string
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      - name: title
        dtype: string
      - name: text
        dtype: string
    splits:
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        num_examples: 432531
    download_size: 37371610
    dataset_size: 159218053
  - config_name: 20230601.zh-yue
    features:
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        dtype: string
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        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
    splits:
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        num_examples: 131542
    download_size: 63294114
    dataset_size: 107325669
  - config_name: 20230601.zu
    features:
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        dtype: string
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        dtype: string
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        dtype: string
    splits:
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        num_examples: 11381
    download_size: 3683813
    dataset_size: 6915666
  - config_name: 20230601.hr
    features:
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    splits:
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    dataset_size: 448338371
  - config_name: 20230601.simple
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    splits:
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        num_bytes: 282844880
        num_examples: 231233
    download_size: 154520600
    dataset_size: 282844880
  - config_name: 20230601.ta
    features:
      - name: id
        dtype: string
      - name: url
        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: train
        num_bytes: 803137068
        num_examples: 156273
    download_size: 261269512
    dataset_size: 803137068

Wikipedia

This Wikipedia dataset contains all available languages for recent dumps. It is a refresh of the 20220301 wikipedia from Huggingface, so it has the same license and dataset card details. The benefits of this dataset are:

• more recent dumps (see table below)
• a few additional languages
• all available languages are preprocessed (including the largests: en and ceb)

version	dump	# available languages	closed & dump	closed & no dump
1.0.0	20230601	328	9: ak (soon), cho, ho, ii, kj, lrc, mh, mus, ng	4: aa, hz, kr, na
	20230901	see you in September...

Source: List of Wikimedia Languages. A few (9) Wikimedias are closed, meaning they won't have new pages, but the dumps are still available. In addition, very few (4) Wikimedias are closed and don't have dumps anymore.

Release Notes

1.0.0

• chore: File layout is now data/{dump}/{lang}/{info.json,*.parquet}. Sorry for the radical update, probably won't happen again.
• chore: Parquet files are now sharded (size < 200 MB), allowing parallel downloads and processing.
• fix: All languages were all processed again because of a bug in the media and category names, leading to some links not being extracted.
• feat: Add en and ceb which were too big for my Beam DirectRunner at the time.

Usage

from datasets import load_dataset

wikipedia_es = load_dataset("graelo/wikipedia", "20230601.es")

---

Build instructions

Developer only. This dataset was preprocessed with a Beam DirectRunner as follows.

1. Determine the date of the dump you are interested in

Choose one wikipedia dump, for instance https://dumps.wikimedia.org/cewiki/ and identify the date.

2. [Optional] Get a refreshed list of languages

This is optional because it not very likely that a new language will have suddenly appeared since the last version and have a significant dataset.

Navigate to https://en.wikipedia.org/wiki/List_of_Wikipedias and copy the languages column from the "Detailed list" table (near the end of the page).

Copy that content in the form of a Python list into lang_def.py (at the top of the repo) under a new date.

3. [Optional] Create Media and Category aliases

In order to properly extract links to images and media in all languages, we must refresh the two corresponding files. To do so, from the root of the repo, run

python -m prep.create_aliases

This will create or update these two files at the root of the repo:

• media_aliases.py
• category_aliases.py

These files are used in the final step

4. Build and prepare the datasets into sharded parquet files

Running this script downloads the wikipedia dumps for each language in lang_def.py and shards each language dataset into the appropriate number of shards (max size ~ 250MB).

python -m prep.build --date 20230601

There are other options:

$ python -m prep.build --help
usage: Wikipedia Builder [-h] [--date DATE] [--language [LANG ...]] [--cache-dir DIR] [--mirror MIRROR]

Prepares the Wikipedia dataset for each language

optional arguments:
  -h, --help             show this help message and exit
  --date DATE            Wikipedia dump date (e.g. 20230601)
  --language [LANG ...]  Language code (e.g. en). If missing, all languages are processed
  --cache-dir DIR        Cache directory for 🤗 Datasets
  --mirror MIRROR        Mirror URL

For instance, for faster downloads of the dumps, use the mirror option:

python -m prep.build \
    --date 20230601 \
    --language bs \
    --mirror https://mirror.accum.se/mirror/wikimedia.org/dumps/

It will download the dumps at around 60MB/s instead of the capped speed (~4MB/s) from https://dumps.wikimedia.org. The script will skip existing directories, allowing you to run the script in several passes.

Notes:

• These instructions build upon the build process of the Wikipedia 🤗 Dataset. HF did a fantastic job, I just pushed it a bit further.
• Be aware that not all mirrors contain all dumps. For instance mirror.accum.se does not contain dumps for languages such as be-x-old or cbk-zam. My own solution is to run a first pass using the aforementioned mirror, and a second pass with the official https://dumps.wikimedia.org site (omitting the --mirror parameter).