Datasets:
Convert dataset to Parquet (#4)
Browse files- Convert dataset to Parquet (cd8cb2dbdbd724c954e04b03748586b54b571581)
- Add arabic data files (eea6a4a1606f4777bd972e6c466ca455e3ba2a26)
- Add chinese data files (c32dce6ec09356c3f54ae2ddf6ccde4a7ecde030)
- Add czech data files (0f6940724607ecee3958925f1cb23c027d1c0aae)
- Add dutch data files (0b65f1ed2d747a576240cb4092c626161c86ea63)
- Add french data files (ddc5b3a971a3ec0d84c6a75458e8d0dcac969fa6)
- Add german data files (2355ac8e32b8c1cbbbdad7a1bc9ad44ec6831932)
- Add hindi data files (9bc9978fefa0624927b2731d1cf9deb337f92228)
- Add indonesian data files (388dd02f242de0e6c63c01abcfa2b85e95b16408)
- Add italian data files (919e7d2a04c444b777d4bf12eb8f5e583019434c)
- Add japanese data files (f150845b9734ef38544a16c030d4a677abac4649)
- Add korean data files (c550a744298751c737743bcf7e8f55f0294f33ee)
- Add portuguese data files (d7d9808c24279d09b1dd16c345dd74f9e2592d52)
- Add russian data files (a77ee278d57072bc52ee7339531cc531c43991f3)
- Add spanish data files (2dba8f024cfd5c6e0176d39eed47ecdf33094395)
- Add thai data files (40dce069d2ba9d3ad1f8c059791087dccf8ac772)
- Add turkish data files (2aa4f7d186a54ef12238c9cc6a8e2d2d3efac573)
- Add vietnamese data files (851acfd6d91040e57b0bdce37de57764b6cc324d)
- Delete loading script (07b31084349cd5ea4e47709288764131db7d6b14)
- Delete data folder (f214d709f9d1ae47e3051fa71c0c0c14e62b01a6)
- README.md +147 -73
- data/arabic.jsonl.gz → arabic/train-00000-of-00001.parquet +2 -2
- data/chinese.jsonl.gz → chinese/train-00000-of-00001.parquet +2 -2
- data/czech.jsonl.gz → czech/train-00000-of-00001.parquet +2 -2
- data/english.jsonl.gz +0 -3
- data/french.jsonl.gz +0 -3
- data/german.jsonl.gz +0 -3
- data/hindi.jsonl.gz +0 -3
- data/indonesian.jsonl.gz +0 -3
- data/italian.jsonl.gz +0 -3
- data/japanese.jsonl.gz +0 -3
- data/korean.jsonl.gz +0 -3
- data/portuguese.jsonl.gz +0 -3
- data/russian.jsonl.gz +0 -3
- data/spanish.jsonl.gz +0 -3
- data/thai.jsonl.gz +0 -3
- data/vietnamese.jsonl.gz +0 -3
- data/dutch.jsonl.gz → dutch/train-00000-of-00001.parquet +2 -2
- english/train-00000-of-00001.parquet +3 -0
- french/train-00000-of-00001.parquet +3 -0
- german/train-00000-of-00001.parquet +3 -0
- hindi/train-00000-of-00001.parquet +3 -0
- indonesian/train-00000-of-00001.parquet +3 -0
- italian/train-00000-of-00001.parquet +3 -0
- japanese/train-00000-of-00001.parquet +3 -0
- korean/train-00000-of-00001.parquet +3 -0
- portuguese/train-00000-of-00001.parquet +3 -0
- russian/train-00000-of-00001.parquet +3 -0
- spanish/train-00000-of-00001.parquet +3 -0
- thai/train-00000-of-00001.parquet +3 -0
- data/turkish.jsonl.gz → turkish/train-00000-of-00001.parquet +2 -2
- vietnamese/train-00000-of-00001.parquet +3 -0
- wiki_lingua.py +0 -168
@@ -36,6 +36,25 @@ task_categories:
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task_ids: []
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paperswithcode_id: wikilingua
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pretty_name: WikiLingua
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dataset_info:
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- config_name: arabic
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features:
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@@ -55,10 +74,10 @@ dataset_info:
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dtype: string
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splits:
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- name: train
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num_bytes:
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num_examples: 9995
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- config_name: chinese
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features:
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- name: url
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dtype: string
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- name: train
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num_examples: 6541
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- config_name: czech
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- name: url
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dtype: string
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- name: train
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num_bytes:
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num_examples: 2520
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- config_name: dutch
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features:
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- name: url
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@@ -121,10 +140,10 @@ dataset_info:
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dtype: string
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splits:
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- name: train
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num_bytes:
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num_examples: 10862
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download_size:
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- config_name: english
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features:
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- name: url
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dtype: string
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- name: train
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num_bytes:
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num_examples: 57945
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download_size:
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- config_name: french
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features:
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- name: url
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dtype: string
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- name: train
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num_bytes:
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num_examples: 21690
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download_size:
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- config_name: german
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features:
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- name: url
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@@ -183,10 +202,10 @@ dataset_info:
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dtype: string
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splits:
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- name: train
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num_bytes:
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num_examples: 20103
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download_size:
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- config_name: hindi
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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num_bytes:
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num_examples: 3402
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download_size:
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- config_name: indonesian
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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num_bytes:
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num_examples: 16308
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download_size:
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dataset_size:
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- config_name: italian
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features:
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- name: url
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@@ -249,10 +268,10 @@ dataset_info:
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dtype: string
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splits:
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- name: train
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num_bytes:
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num_examples: 17673
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download_size:
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- config_name: japanese
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features:
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- name: url
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@@ -271,10 +290,10 @@ dataset_info:
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dtype: string
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splits:
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- name: train
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num_bytes:
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num_examples: 4372
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download_size:
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dataset_size:
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- config_name: korean
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features:
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- name: url
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@@ -293,10 +312,10 @@ dataset_info:
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dtype: string
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splits:
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- name: train
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num_bytes:
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num_examples: 4111
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- config_name: portuguese
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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num_bytes:
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num_examples: 28143
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- config_name: russian
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features:
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- name: url
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@@ -337,10 +356,10 @@ dataset_info:
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dtype: string
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splits:
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- name: train
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num_examples: 18143
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- config_name: spanish
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features:
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- name: url
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@@ -359,10 +378,10 @@ dataset_info:
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dtype: string
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splits:
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- name: train
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num_bytes:
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num_examples: 38795
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- config_name: thai
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features:
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- name: url
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@@ -381,10 +400,10 @@ dataset_info:
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dtype: string
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- name: train
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num_bytes:
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num_examples: 5093
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- config_name: turkish
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features:
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- name: url
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@@ -403,10 +422,10 @@ dataset_info:
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dtype: string
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- name: train
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num_examples: 1512
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- config_name: vietnamese
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features:
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- name: url
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@@ -425,29 +444,84 @@ dataset_info:
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dtype: string
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splits:
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- name: train
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num_examples: 6616
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- arabic
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---
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# Dataset Card for "wiki_lingua"
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task_ids: []
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paperswithcode_id: wikilingua
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pretty_name: WikiLingua
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+
config_names:
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- arabic
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- chinese
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- czech
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- dutch
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- english
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- french
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- german
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- hindi
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- indonesian
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- italian
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- japanese
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- korean
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- portuguese
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- russian
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- spanish
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- thai
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- turkish
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- vietnamese
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dataset_info:
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- config_name: arabic
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features:
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dtype: string
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splits:
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- name: train
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num_bytes: 119116075
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num_examples: 9995
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download_size: 55808460
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dataset_size: 119116075
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- config_name: chinese
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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num_bytes: 41170645
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num_examples: 6541
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download_size: 25187026
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dataset_size: 41170645
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- config_name: czech
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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num_bytes: 20816346
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num_examples: 2520
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download_size: 12480761
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dataset_size: 20816346
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- config_name: dutch
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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num_bytes: 87257952
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num_examples: 10862
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download_size: 47651076
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dataset_size: 87257952
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- config_name: english
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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num_bytes: 333699946
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num_examples: 57945
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download_size: 187189233
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dataset_size: 333699946
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- config_name: french
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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+
num_bytes: 197550244
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num_examples: 21690
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download_size: 105158840
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dataset_size: 197550244
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- config_name: german
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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+
num_bytes: 168674208
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num_examples: 20103
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+
download_size: 93078076
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dataset_size: 168674208
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- config_name: hindi
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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+
num_bytes: 63785007
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num_examples: 3402
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download_size: 22774620
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dataset_size: 63785007
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- config_name: indonesian
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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+
num_bytes: 136408773
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num_examples: 16308
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download_size: 67658970
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dataset_size: 136408773
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- config_name: italian
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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+
num_bytes: 138119439
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num_examples: 17673
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+
download_size: 78108134
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dataset_size: 138119439
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- config_name: japanese
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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+
num_bytes: 40144987
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num_examples: 4372
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download_size: 19794488
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dataset_size: 40144987
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- config_name: korean
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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+
num_bytes: 38647570
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num_examples: 4111
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download_size: 20029486
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dataset_size: 38647570
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- config_name: portuguese
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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num_bytes: 204270713
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num_examples: 28143
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download_size: 114735912
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dataset_size: 204270713
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- config_name: russian
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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num_bytes: 241923944
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num_examples: 18143
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download_size: 111025228
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dataset_size: 241923944
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- config_name: spanish
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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num_bytes: 314618442
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num_examples: 38795
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download_size: 170995186
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dataset_size: 314618442
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- config_name: thai
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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num_bytes: 86982807
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num_examples: 5093
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download_size: 31944979
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dataset_size: 86982807
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- config_name: turkish
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features:
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- name: url
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dtype: string
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splits:
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- name: train
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num_bytes: 11371777
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num_examples: 1512
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download_size: 5964904
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dataset_size: 11371777
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- config_name: vietnamese
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features:
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- name: url
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dtype: string
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splits:
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446 |
- name: train
|
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+
num_bytes: 69868744
|
448 |
num_examples: 6616
|
449 |
+
download_size: 33194150
|
450 |
+
dataset_size: 69868744
|
451 |
+
configs:
|
452 |
+
- config_name: arabic
|
453 |
+
data_files:
|
454 |
+
- split: train
|
455 |
+
path: arabic/train-*
|
456 |
+
- config_name: chinese
|
457 |
+
data_files:
|
458 |
+
- split: train
|
459 |
+
path: chinese/train-*
|
460 |
+
- config_name: czech
|
461 |
+
data_files:
|
462 |
+
- split: train
|
463 |
+
path: czech/train-*
|
464 |
+
- config_name: dutch
|
465 |
+
data_files:
|
466 |
+
- split: train
|
467 |
+
path: dutch/train-*
|
468 |
+
- config_name: english
|
469 |
+
data_files:
|
470 |
+
- split: train
|
471 |
+
path: english/train-*
|
472 |
+
default: true
|
473 |
+
- config_name: french
|
474 |
+
data_files:
|
475 |
+
- split: train
|
476 |
+
path: french/train-*
|
477 |
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- config_name: german
|
478 |
+
data_files:
|
479 |
+
- split: train
|
480 |
+
path: german/train-*
|
481 |
+
- config_name: hindi
|
482 |
+
data_files:
|
483 |
+
- split: train
|
484 |
+
path: hindi/train-*
|
485 |
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- config_name: indonesian
|
486 |
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data_files:
|
487 |
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- split: train
|
488 |
+
path: indonesian/train-*
|
489 |
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- config_name: italian
|
490 |
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data_files:
|
491 |
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- split: train
|
492 |
+
path: italian/train-*
|
493 |
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- config_name: japanese
|
494 |
+
data_files:
|
495 |
+
- split: train
|
496 |
+
path: japanese/train-*
|
497 |
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- config_name: korean
|
498 |
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data_files:
|
499 |
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- split: train
|
500 |
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path: korean/train-*
|
501 |
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- config_name: portuguese
|
502 |
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data_files:
|
503 |
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- split: train
|
504 |
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path: portuguese/train-*
|
505 |
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- config_name: russian
|
506 |
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data_files:
|
507 |
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- split: train
|
508 |
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path: russian/train-*
|
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- config_name: spanish
|
510 |
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data_files:
|
511 |
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- split: train
|
512 |
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path: spanish/train-*
|
513 |
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- config_name: thai
|
514 |
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data_files:
|
515 |
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- split: train
|
516 |
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path: thai/train-*
|
517 |
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- config_name: turkish
|
518 |
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data_files:
|
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- split: train
|
520 |
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path: turkish/train-*
|
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- config_name: vietnamese
|
522 |
+
data_files:
|
523 |
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- split: train
|
524 |
+
path: vietnamese/train-*
|
525 |
---
|
526 |
# Dataset Card for "wiki_lingua"
|
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|
|
1 |
-
# coding=utf-8
|
2 |
-
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
|
3 |
-
#
|
4 |
-
# Licensed under the Apache License, Version 2.0 (the "License");
|
5 |
-
# you may not use this file except in compliance with the License.
|
6 |
-
# You may obtain a copy of the License at
|
7 |
-
#
|
8 |
-
# http://www.apache.org/licenses/LICENSE-2.0
|
9 |
-
#
|
10 |
-
# Unless required by applicable law or agreed to in writing, software
|
11 |
-
# distributed under the License is distributed on an "AS IS" BASIS,
|
12 |
-
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
13 |
-
# See the License for the specific language governing permissions and
|
14 |
-
# limitations under the License.
|
15 |
-
"""WikiLingua."""
|
16 |
-
|
17 |
-
|
18 |
-
import json
|
19 |
-
|
20 |
-
import datasets
|
21 |
-
|
22 |
-
|
23 |
-
# Find for instance the citation on arxiv or on the dataset repo/website
|
24 |
-
_CITATION = """\
|
25 |
-
@inproceedings{ladhak-etal-2020-wikilingua,
|
26 |
-
title = "{W}iki{L}ingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarization",
|
27 |
-
author = "Ladhak, Faisal and
|
28 |
-
Durmus, Esin and
|
29 |
-
Cardie, Claire and
|
30 |
-
McKeown, Kathleen",
|
31 |
-
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
|
32 |
-
month = nov,
|
33 |
-
year = "2020",
|
34 |
-
address = "Online",
|
35 |
-
publisher = "Association for Computational Linguistics",
|
36 |
-
url = "https://aclanthology.org/2020.findings-emnlp.360",
|
37 |
-
doi = "10.18653/v1/2020.findings-emnlp.360",
|
38 |
-
pages = "4034--4048",
|
39 |
-
}
|
40 |
-
"""
|
41 |
-
|
42 |
-
_DESCRIPTION = """\
|
43 |
-
WikiLingua is a large-scale multilingual dataset for the evaluation of
|
44 |
-
cross-lingual abstractive summarization systems. The dataset includes ~770k
|
45 |
-
article and summary pairs in 18 languages from WikiHow. The gold-standard
|
46 |
-
article-summary alignments across languages was done by aligning the images
|
47 |
-
that are used to describe each how-to step in an article.
|
48 |
-
"""
|
49 |
-
|
50 |
-
_HOMEPAGE = "https://github.com/esdurmus/Wikilingua"
|
51 |
-
|
52 |
-
_LICENSE = "CC BY-NC-SA 3.0"
|
53 |
-
|
54 |
-
# Download link
|
55 |
-
_URL = "data/{language}.jsonl.gz"
|
56 |
-
_LANGUAGES = [
|
57 |
-
"arabic",
|
58 |
-
"chinese",
|
59 |
-
"czech",
|
60 |
-
"dutch",
|
61 |
-
"english",
|
62 |
-
"french",
|
63 |
-
"german",
|
64 |
-
"hindi",
|
65 |
-
"indonesian",
|
66 |
-
"italian",
|
67 |
-
"japanese",
|
68 |
-
"korean",
|
69 |
-
"portuguese",
|
70 |
-
"russian",
|
71 |
-
"spanish",
|
72 |
-
"thai",
|
73 |
-
"turkish",
|
74 |
-
"vietnamese",
|
75 |
-
]
|
76 |
-
|
77 |
-
|
78 |
-
class WikiLingua(datasets.GeneratorBasedBuilder):
|
79 |
-
"""WikiLingua dataset."""
|
80 |
-
|
81 |
-
VERSION = datasets.Version("1.1.1")
|
82 |
-
|
83 |
-
BUILDER_CONFIGS = [
|
84 |
-
datasets.BuilderConfig(
|
85 |
-
name=lang,
|
86 |
-
version=datasets.Version("1.1.1"),
|
87 |
-
description=f"A subset of article-summary in {lang.capitalize()}",
|
88 |
-
)
|
89 |
-
for lang in _LANGUAGES
|
90 |
-
]
|
91 |
-
|
92 |
-
DEFAULT_CONFIG_NAME = "english"
|
93 |
-
|
94 |
-
def _info(self):
|
95 |
-
if self.config.name == "english":
|
96 |
-
features = datasets.Features(
|
97 |
-
{
|
98 |
-
"url": datasets.Value("string"),
|
99 |
-
"article": datasets.Sequence(
|
100 |
-
{
|
101 |
-
"section_name": datasets.Value("string"),
|
102 |
-
"document": datasets.Value("string"),
|
103 |
-
"summary": datasets.Value("string"),
|
104 |
-
}
|
105 |
-
),
|
106 |
-
}
|
107 |
-
)
|
108 |
-
else:
|
109 |
-
features = datasets.Features(
|
110 |
-
{
|
111 |
-
"url": datasets.Value("string"),
|
112 |
-
"article": datasets.Sequence(
|
113 |
-
{
|
114 |
-
"section_name": datasets.Value("string"),
|
115 |
-
"document": datasets.Value("string"),
|
116 |
-
"summary": datasets.Value("string"),
|
117 |
-
"english_url": datasets.Value("string"),
|
118 |
-
"english_section_name": datasets.Value("string"),
|
119 |
-
}
|
120 |
-
),
|
121 |
-
}
|
122 |
-
)
|
123 |
-
|
124 |
-
return datasets.DatasetInfo(
|
125 |
-
# This is the description that will appear on the datasets page.
|
126 |
-
description=_DESCRIPTION,
|
127 |
-
# This defines the different columns of the dataset and their types
|
128 |
-
features=features, # Here we define them above because they are different between the two configurations
|
129 |
-
# Homepage of the dataset for documentation
|
130 |
-
homepage=_HOMEPAGE,
|
131 |
-
# License for the dataset if available
|
132 |
-
license=_LICENSE,
|
133 |
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# Citation for the dataset
|
134 |
-
citation=_CITATION,
|
135 |
-
)
|
136 |
-
|
137 |
-
def _split_generators(self, dl_manager):
|
138 |
-
"""Returns SplitGenerators."""
|
139 |
-
filepath = dl_manager.download_and_extract(_URL.format(language=self.config.name))
|
140 |
-
return [
|
141 |
-
datasets.SplitGenerator(
|
142 |
-
name=datasets.Split.TRAIN,
|
143 |
-
# These kwargs will be passed to _generate_examples
|
144 |
-
gen_kwargs={
|
145 |
-
"filepath": filepath,
|
146 |
-
},
|
147 |
-
),
|
148 |
-
]
|
149 |
-
|
150 |
-
def _process_article(self, article):
|
151 |
-
"""Parse the article and convert into list of dict"""
|
152 |
-
processed_article = []
|
153 |
-
for key, value in article.items():
|
154 |
-
row = {"section_name": key, "document": value["document"], "summary": value["summary"]}
|
155 |
-
|
156 |
-
if self.config.name != "english":
|
157 |
-
row["english_url"] = value["english_url"]
|
158 |
-
row["english_section_name"] = value["english_section_name"]
|
159 |
-
processed_article.append(row)
|
160 |
-
|
161 |
-
return processed_article
|
162 |
-
|
163 |
-
def _generate_examples(self, filepath):
|
164 |
-
"""Yields examples."""
|
165 |
-
with open(filepath, "rb") as f:
|
166 |
-
for id_, line in enumerate(f):
|
167 |
-
row = json.loads(line)
|
168 |
-
yield id_, {"url": row["url"], "article": self._process_article(row["article"])}
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