Update files from the datasets library (from 1.16.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.16.0

README.md

@@ -1,7 +1,629 @@
 ---
-languages:
-- en
+annotations_creators:
+- no-annotation
+language_creators:
+- crowdsourced
+pretty_name: Wikipedia
 paperswithcode_id: null
+licenses:
+- cc-by-sa-3-0
+- gfdl-1-3-or-later
+task_categories:
+- sequence-modeling
+task_ids:
+- language-modeling
+source_datasets:
+- original
+multilinguality:
+- multilingual
+size_categories:
+- n<1K
+- 1K<n<10K
+- 10K<n<100K
+- 100K<n<1M
+- 1M<n<10M
+- 10M<n<100M
+languages:
+  20200501-aa:
+  - aa
+  20200501-ab:
+  - ab
+  20200501-ace:
+  - ace
+  20200501-ady:
+  - unknown
+  20200501-af:
+  - af
+  20200501-ak:
+  - ak
+  20200501-als:
+  - als
+  20200501-am:
+  - am
+  20200501-an:
+  - an
+  20200501-ang:
+  - ang
+  20200501-ar:
+  - ar
+  20200501-arc:
+  - arc
+  20200501-arz:
+  - arz
+  20200501-as:
+  - as
+  20200501-ast:
+  - ast
+  20200501-atj:
+  - atj
+  20200501-av:
+  - av
+  20200501-ay:
+  - ay
+  20200501-az:
+  - az
+  20200501-azb:
+  - azb
+  20200501-ba:
+  - ba
+  20200501-bar:
+  - bar
+  20200501-bat-smg:
+  - sgs
+  20200501-bcl:
+  - bcl
+  20200501-be:
+  - be
+  20200501-be-x-old:
+  - unknown
+  20200501-bg:
+  - bg
+  20200501-bh:
+  - bh
+  20200501-bi:
+  - bi
+  20200501-bjn:
+  - bjn
+  20200501-bm:
+  - bm
+  20200501-bn:
+  - bn
+  20200501-bo:
+  - bo
+  20200501-bpy:
+  - bpy
+  20200501-br:
+  - br
+  20200501-bs:
+  - bs
+  20200501-bug:
+  - bug
+  20200501-bxr:
+  - bxr
+  20200501-ca:
+  - ca
+  20200501-cbk-zam:
+  - cbk
+  20200501-cdo:
+  - cdo
+  20200501-ce:
+  - ce
+  20200501-ceb:
+  - ceb
+  20200501-ch:
+  - ch
+  20200501-cho:
+  - cho
+  20200501-chr:
+  - chr
+  20200501-chy:
+  - chy
+  20200501-ckb:
+  - ckb
+  20200501-co:
+  - co
+  20200501-cr:
+  - cr
+  20200501-crh:
+  - crh
+  20200501-cs:
+  - cs
+  20200501-csb:
+  - csb
+  20200501-cu:
+  - cu
+  20200501-cv:
+  - cv
+  20200501-cy:
+  - cy
+  20200501-da:
+  - da
+  20200501-de:
+  - de
+  20200501-din:
+  - din
+  20200501-diq:
+  - diq
+  20200501-dsb:
+  - dsb
+  20200501-dty:
+  - dty
+  20200501-dv:
+  - dv
+  20200501-dz:
+  - dz
+  20200501-ee:
+  - ee
+  20200501-el:
+  - el
+  20200501-eml:
+  - eml
+  20200501-en:
+  - en
+  20200501-eo:
+  - eo
+  20200501-es:
+  - es
+  20200501-et:
+  - et
+  20200501-eu:
+  - eu
+  20200501-ext:
+  - ext
+  20200501-fa:
+  - fa
+  20200501-ff:
+  - ff
+  20200501-fi:
+  - fi
+  20200501-fiu-vro:
+  - vro
+  20200501-fj:
+  - fj
+  20200501-fo:
+  - fo
+  20200501-fr:
+  - fr
+  20200501-frp:
+  - frp
+  20200501-frr:
+  - frr
+  20200501-fur:
+  - fur
+  20200501-fy:
+  - fy
+  20200501-ga:
+  - ga
+  20200501-gag:
+  - gag
+  20200501-gan:
+  - gan
+  20200501-gd:
+  - gd
+  20200501-gl:
+  - gl
+  20200501-glk:
+  - glk
+  20200501-gn:
+  - gn
+  20200501-gom:
+  - gom
+  20200501-gor:
+  - gor
+  20200501-got:
+  - got
+  20200501-gu:
+  - gu
+  20200501-gv:
+  - gv
+  20200501-ha:
+  - ha
+  20200501-hak:
+  - hak
+  20200501-haw:
+  - haw
+  20200501-he:
+  - he
+  20200501-hi:
+  - hi
+  20200501-hif:
+  - hif
+  20200501-ho:
+  - ho
+  20200501-hr:
+  - hr
+  20200501-hsb:
+  - hsb
+  20200501-ht:
+  - ht
+  20200501-hu:
+  - hu
+  20200501-hy:
+  - hy
+  20200501-ia:
+  - ia
+  20200501-id:
+  - id
+  20200501-ie:
+  - ie
+  20200501-ig:
+  - ig
+  20200501-ii:
+  - ii
+  20200501-ik:
+  - ik
+  20200501-ilo:
+  - ilo
+  20200501-inh:
+  - inh
+  20200501-io:
+  - io
+  20200501-is:
+  - is
+  20200501-it:
+  - it
+  20200501-iu:
+  - iu
+  20200501-ja:
+  - ja
+  20200501-jam:
+  - jam
+  20200501-jbo:
+  - jbo
+  20200501-jv:
+  - jv
+  20200501-ka:
+  - ka
+  20200501-kaa:
+  - kaa
+  20200501-kab:
+  - kab
+  20200501-kbd:
+  - kbd
+  20200501-kbp:
+  - kbp
+  20200501-kg:
+  - kg
+  20200501-ki:
+  - ki
+  20200501-kj:
+  - kj
+  20200501-kk:
+  - kk
+  20200501-kl:
+  - kl
+  20200501-km:
+  - km
+  20200501-kn:
+  - kn
+  20200501-ko:
+  - ko
+  20200501-koi:
+  - koi
+  20200501-krc:
+  - krc
+  20200501-ks:
+  - ks
+  20200501-ksh:
+  - ksh
+  20200501-ku:
+  - ku
+  20200501-kv:
+  - kv
+  20200501-kw:
+  - kw
+  20200501-ky:
+  - ky
+  20200501-la:
+  - la
+  20200501-lad:
+  - lad
+  20200501-lb:
+  - lb
+  20200501-lbe:
+  - lbe
+  20200501-lez:
+  - lez
+  20200501-lfn:
+  - lfn
+  20200501-lg:
+  - lg
+  20200501-li:
+  - li
+  20200501-lij:
+  - lij
+  20200501-lmo:
+  - lmo
+  20200501-ln:
+  - ln
+  20200501-lo:
+  - lo
+  20200501-lrc:
+  - lrc
+  20200501-lt:
+  - lt
+  20200501-ltg:
+  - ltg
+  20200501-lv:
+  - lv
+  20200501-mai:
+  - mai
+  20200501-map-bms:
+  - unknown
+  20200501-mdf:
+  - mdf
+  20200501-mg:
+  - mg
+  20200501-mh:
+  - mh
+  20200501-mhr:
+  - mhr
+  20200501-mi:
+  - mi
+  20200501-min:
+  - min
+  20200501-mk:
+  - mk
+  20200501-ml:
+  - ml
+  20200501-mn:
+  - mn
+  20200501-mr:
+  - mr
+  20200501-mrj:
+  - mrj
+  20200501-ms:
+  - ms
+  20200501-mt:
+  - mt
+  20200501-mus:
+  - mus
+  20200501-mwl:
+  - mwl
+  20200501-my:
+  - my
+  20200501-myv:
+  - myv
+  20200501-mzn:
+  - mzn
+  20200501-na:
+  - na
+  20200501-nah:
+  - nah
+  20200501-nap:
+  - nap
+  20200501-nds:
+  - nds
+  20200501-nds-nl:
+  - nds-nl
+  20200501-ne:
+  - ne
+  20200501-new:
+  - new
+  20200501-ng:
+  - ng
+  20200501-nl:
+  - nl
+  20200501-nn:
+  - nn
+  20200501-no:
+  - "no"
+  20200501-nov:
+  - nov
+  20200501-nrm:
+  - nrf
+  20200501-nso:
+  - nso
+  20200501-nv:
+  - nv
+  20200501-ny:
+  - ny
+  20200501-oc:
+  - oc
+  20200501-olo:
+  - olo
+  20200501-om:
+  - om
+  20200501-or:
+  - or
+  20200501-os:
+  - os
+  20200501-pa:
+  - pa
+  20200501-pag:
+  - pag
+  20200501-pam:
+  - pam
+  20200501-pap:
+  - pap
+  20200501-pcd:
+  - pcd
+  20200501-pdc:
+  - pdc
+  20200501-pfl:
+  - pfl
+  20200501-pi:
+  - pi
+  20200501-pih:
+  - pih
+  20200501-pl:
+  - pl
+  20200501-pms:
+  - pms
+  20200501-pnb:
+  - pnb
+  20200501-pnt:
+  - pnt
+  20200501-ps:
+  - ps
+  20200501-pt:
+  - pt
+  20200501-qu:
+  - qu
+  20200501-rm:
+  - rm
+  20200501-rmy:
+  - rmy
+  20200501-rn:
+  - rn
+  20200501-ro:
+  - ro
+  20200501-roa-rup:
+  - rup
+  20200501-roa-tara:
+  - unknown
+  20200501-ru:
+  - ru
+  20200501-rue:
+  - rue
+  20200501-rw:
+  - rw
+  20200501-sa:
+  - sa
+  20200501-sah:
+  - sah
+  20200501-sat:
+  - sat
+  20200501-sc:
+  - sc
+  20200501-scn:
+  - scn
+  20200501-sco:
+  - sco
+  20200501-sd:
+  - sd
+  20200501-se:
+  - se
+  20200501-sg:
+  - sg
+  20200501-sh:
+  - sh
+  20200501-si:
+  - si
+  20200501-simple:
+  - simple
+  20200501-sk:
+  - sk
+  20200501-sl:
+  - sl
+  20200501-sm:
+  - sm
+  20200501-sn:
+  - sn
+  20200501-so:
+  - so
+  20200501-sq:
+  - sq
+  20200501-sr:
+  - sr
+  20200501-srn:
+  - srn
+  20200501-ss:
+  - ss
+  20200501-st:
+  - st
+  20200501-stq:
+  - stq
+  20200501-su:
+  - su
+  20200501-sv:
+  - sv
+  20200501-sw:
+  - sw
+  20200501-szl:
+  - szl
+  20200501-ta:
+  - ta
+  20200501-tcy:
+  - tcy
+  20200501-te:
+  - te
+  20200501-tet:
+  - tdt
+  20200501-tg:
+  - tg
+  20200501-th:
+  - th
+  20200501-ti:
+  - ti
+  20200501-tk:
+  - tk
+  20200501-tl:
+  - tl
+  20200501-tn:
+  - tn
+  20200501-to:
+  - to
+  20200501-tpi:
+  - tpi
+  20200501-tr:
+  - tr
+  20200501-ts:
+  - ts
+  20200501-tt:
+  - tt
+  20200501-tum:
+  - tum
+  20200501-tw:
+  - tw
+  20200501-ty:
+  - ty
+  20200501-tyv:
+  - tyv
+  20200501-udm:
+  - udm
+  20200501-ug:
+  - ug
+  20200501-uk:
+  - uk
+  20200501-ur:
+  - ur
+  20200501-uz:
+  - uz
+  20200501-ve:
+  - ve
+  20200501-vec:
+  - vec
+  20200501-vep:
+  - vep
+  20200501-vi:
+  - vi
+  20200501-vls:
+  - vls
+  20200501-vo:
+  - vo
+  20200501-wa:
+  - wa
+  20200501-war:
+  - war
+  20200501-wo:
+  - wo
+  20200501-wuu:
+  - wuu
+  20200501-xal:
+  - xal
+  20200501-xh:
+  - xh
+  20200501-xmf:
+  - xmf
+  20200501-yi:
+  - yi
+  20200501-yo:
+  - yo
+  20200501-za:
+  - za
+  20200501-zea:
+  - zea
+  20200501-zh:
+  - zh
+  20200501-zh-classical:
+  - lzh
+  20200501-zh-min-nan:
+  - nan
+  20200501-zh-yue:
+  - yue
+  20200501-zu:
+  - zu
 ---
 
 # Dataset Card for "wikipedia"
@@ -48,6 +670,8 @@ The datasets are built from the Wikipedia dump
 contains the content of one full Wikipedia article with cleaning to strip
 markdown and unwanted sections (references, etc.).
 
+The articles have been parsed using the ``mwparserfromhell`` tool.
+
 ### Supported Tasks and Leaderboards
 
 [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
@@ -62,16 +686,6 @@ We show detailed information for up to 5 configurations of the dataset.
 
 ### Data Instances
 
-#### 20200501.de
-
-- **Size of downloaded dataset files:** 5531.82 MB
-- **Size of the generated dataset:** 7716.79 MB
-- **Total amount of disk used:** 13248.61 MB
-
-An example of 'train' looks as follows.
-```
-
-```
 
 #### 20200501.en
 
@@ -79,70 +693,52 @@ An example of 'train' looks as follows.
 - **Size of the generated dataset:** 17481.07 MB
 - **Total amount of disk used:** 34877.35 MB
 
-An example of 'train' looks as follows.
+An example looks as follows.
 ```
-
+{
+  'title': 'Yangliuqing',
+  'text': 'Yangliuqing () is a market town in Xiqing District, in the western suburbs of Tianjin,
+     ...
+     and traditional period furnishings and crafts.\n\nSee also \n\nList of township-level divisions of Tianjin\n\nReferences \n\n
+     http://arts.cultural-china.com/en/65Arts4795.html\n\nCategory:Towns in Tianjin'
+}
 ```
 
+#### 20200501.de
+
+- **Size of downloaded dataset files:** 5531.82 MB
+- **Size of the generated dataset:** 7716.79 MB
+- **Total amount of disk used:** 13248.61 MB
+
 #### 20200501.fr
 
 - **Size of downloaded dataset files:** 4653.55 MB
 - **Size of the generated dataset:** 6182.24 MB
 - **Total amount of disk used:** 10835.79 MB
 
-An example of 'train' looks as follows.
-```
-
-```
-
 #### 20200501.frr
 
 - **Size of downloaded dataset files:** 9.05 MB
 - **Size of the generated dataset:** 5.88 MB
 - **Total amount of disk used:** 14.93 MB
 
-An example of 'train' looks as follows.
-```
-
-```
-
 #### 20200501.it
 
 - **Size of downloaded dataset files:** 2970.57 MB
 - **Size of the generated dataset:** 3809.89 MB
 - **Total amount of disk used:** 6780.46 MB
 
-An example of 'train' looks as follows.
-```
-
-```
-
 ### Data Fields
 
-The data fields are the same among all splits.
+The data fields are the same among all splits and configurations:
 
-#### 20200501.de
-- `title`: a `string` feature.
-- `text`: a `string` feature.
-
-#### 20200501.en
-- `title`: a `string` feature.
-- `text`: a `string` feature.
-
-#### 20200501.fr
-- `title`: a `string` feature.
-- `text`: a `string` feature.
-
-#### 20200501.frr
-- `title`: a `string` feature.
-- `text`: a `string` feature.
-
-#### 20200501.it
-- `title`: a `string` feature.
-- `text`: a `string` feature.
+- `title`: a `string` feature corresponding to the title of the article
+- `text`: a `string` feature corresponding to the text content of the article
 
 ### Data Splits
 
+Here are the sizes for several configurations:
+
 |    name    | train |
 |------------|------:|
 |20200501.de |3140341|

wikipedia.py

@@ -374,8 +374,8 @@ class WikipediaConfig(datasets.BuilderConfig):
           **kwargs: keyword arguments forwarded to super.
         """
         super(WikipediaConfig, self).__init__(
-            name="{0}.{1}".format(date, language),
-            description="Wikipedia dataset for {0}, parsed from {1} dump.".format(language, date),
+            name=f"{date}.{language}",
+            description=f"Wikipedia dataset for {language}, parsed from {date} dump.",
             **kwargs,
         )
         self.date = date
@@ -465,16 +465,16 @@ class Wikipedia(datasets.BeamBasedBuilder):
                     if not elem.tag.endswith("page"):
                         continue
                     namespace = elem.tag[:-4]
-                    title = elem.find("./{0}title".format(namespace)).text
-                    ns = elem.find("./{0}ns".format(namespace)).text
-                    id_ = elem.find("./{0}id".format(namespace)).text
+                    title = elem.find(f"./{namespace}title").text
+                    ns = elem.find(f"./{namespace}ns").text
+                    id_ = elem.find(f"./{namespace}id").text
 
                     # Filter pages that are not in the "main" namespace.
                     if ns != "0":
                         elem.clear()
                         continue
 
-                    raw_content = elem.find("./{0}revision/{0}text".format(namespace)).text
+                    raw_content = elem.find(f"./{namespace}revision/{namespace}text").text
                     elem.clear()
 
                     # Filter redirects.