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--- |
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language: |
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- multilingual |
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- af |
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- am |
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- ar |
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- as |
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- az |
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- be |
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- bg |
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- bn |
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- br |
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- bs |
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- ca |
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- cs |
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- cy |
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- da |
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- de |
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- el |
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- en |
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- eo |
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- es |
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- et |
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- eu |
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- fa |
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- fi |
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- fr |
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- fy |
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- ga |
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- gd |
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- gl |
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- gu |
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- ha |
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- he |
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- hi |
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- hr |
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- hu |
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- hy |
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- id |
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- is |
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- it |
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- ja |
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- jv |
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- ka |
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- kk |
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- km |
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- kn |
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- ko |
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- ku |
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- ky |
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- la |
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- lo |
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- lt |
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- lv |
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- mg |
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- mk |
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- ml |
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- mn |
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- mr |
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- ms |
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- my |
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- ne |
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- nl |
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- 'no' |
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- om |
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- or |
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- pa |
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- pl |
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- ps |
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- pt |
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- ro |
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- ru |
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- sa |
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- sd |
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- si |
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- sk |
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- sl |
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- so |
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- sq |
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- sr |
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- su |
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- sv |
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- sw |
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- ta |
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- te |
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- th |
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- tl |
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- tr |
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- ug |
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- uk |
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- ur |
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- uz |
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- vi |
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- xh |
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- yi |
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- zh |
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pretty_name: All of Common Crawl News, 100+ languages, preprocessed and cleaned |
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task_categories: |
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- text-classification |
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- question-answering |
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- text-generation |
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- text2text-generation |
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size_categories: |
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- 100M<n<1B |
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tags: |
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- news |
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configs: |
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- config_name: "2016" |
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data_files: "2016_part_00.jsonl.gz" |
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- config_name: "2017" |
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data_files: |
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- "2017_part_00.jsonl.gz" |
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- "2017_part_01.jsonl.gz" |
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- "2017_part_02.jsonl.gz" |
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- "2017_part_03.jsonl.gz" |
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- "2017_part_04.jsonl.gz" |
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- "2017_part_05.jsonl.gz" |
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- config_name: "2018" |
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data_files: |
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- "2018_part_00.jsonl.gz" |
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- "2018_part_01.jsonl.gz" |
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- "2018_part_02.jsonl.gz" |
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- "2018_part_03.jsonl.gz" |
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- "2018_part_04.jsonl.gz" |
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- "2018_part_05.jsonl.gz" |
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- "2018_part_06.jsonl.gz" |
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- "2018_part_07.jsonl.gz" |
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- "2018_part_08.jsonl.gz" |
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- config_name: "2019" |
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data_files: |
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- "2019_part_00.jsonl.gz" |
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- "2019_part_01.jsonl.gz" |
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- "2019_part_02.jsonl.gz" |
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- "2019_part_03.jsonl.gz" |
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- "2019_part_04.jsonl.gz" |
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- "2019_part_05.jsonl.gz" |
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- "2019_part_06.jsonl.gz" |
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- "2019_part_07.jsonl.gz" |
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- "2019_part_08.jsonl.gz" |
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- "2019_part_09.jsonl.gz" |
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- "2019_part_10.jsonl.gz" |
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- config_name: "2020" |
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data_files: |
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- "2020_part_00.jsonl.gz" |
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- "2020_part_01.jsonl.gz" |
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- "2020_part_02.jsonl.gz" |
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- "2020_part_03.jsonl.gz" |
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- "2020_part_04.jsonl.gz" |
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- "2020_part_05.jsonl.gz" |
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- "2020_part_06.jsonl.gz" |
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- "2020_part_07.jsonl.gz" |
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- "2020_part_08.jsonl.gz" |
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- "2020_part_09.jsonl.gz" |
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- "2020_part_10.jsonl.gz" |
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- "2020_part_11.jsonl.gz" |
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- "2020_part_12.jsonl.gz" |
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- "2020_part_13.jsonl.gz" |
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- "2020_part_14.jsonl.gz" |
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- "2020_part_15.jsonl.gz" |
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- config_name: "2021" |
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data_files: |
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- "2021_part_00.jsonl.gz" |
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- "2021_part_01.jsonl.gz" |
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- "2021_part_02.jsonl.gz" |
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- "2021_part_03.jsonl.gz" |
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- "2021_part_04.jsonl.gz" |
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- "2021_part_05.jsonl.gz" |
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- "2021_part_06.jsonl.gz" |
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- "2021_part_07.jsonl.gz" |
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- "2021_part_08.jsonl.gz" |
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- "2021_part_09.jsonl.gz" |
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- "2021_part_10.jsonl.gz" |
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- "2021_part_11.jsonl.gz" |
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- "2021_part_12.jsonl.gz" |
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- "2021_part_13.jsonl.gz" |
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- "2021_part_14.jsonl.gz" |
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- "2021_part_15.jsonl.gz" |
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- config_name: "2022" |
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data_files: |
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- "2022_part_00.jsonl.gz" |
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- "2022_part_01.jsonl.gz" |
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- "2022_part_02.jsonl.gz" |
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- "2022_part_03.jsonl.gz" |
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- "2022_part_04.jsonl.gz" |
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- "2022_part_05.jsonl.gz" |
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- "2022_part_06.jsonl.gz" |
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- "2022_part_07.jsonl.gz" |
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- "2022_part_08.jsonl.gz" |
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- "2022_part_09.jsonl.gz" |
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- "2022_part_10.jsonl.gz" |
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- "2022_part_11.jsonl.gz" |
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- "2022_part_12.jsonl.gz" |
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- "2022_part_13.jsonl.gz" |
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- "2022_part_14.jsonl.gz" |
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- "2022_part_15.jsonl.gz" |
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- "2022_part_16.jsonl.gz" |
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- config_name: "2023" |
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data_files: |
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- "2023_part_00.jsonl.gz" |
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- "2023_part_01.jsonl.gz" |
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- "2023_part_02.jsonl.gz" |
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- "2023_part_03.jsonl.gz" |
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- "2023_part_04.jsonl.gz" |
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- "2023_part_05.jsonl.gz" |
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- "2023_part_06.jsonl.gz" |
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- "2023_part_07.jsonl.gz" |
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- "2023_part_08.jsonl.gz" |
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- "2023_part_09.jsonl.gz" |
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- "2023_part_10.jsonl.gz" |
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- "2023_part_11.jsonl.gz" |
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- "2023_part_12.jsonl.gz" |
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- "2023_part_13.jsonl.gz" |
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- "2023_part_14.jsonl.gz" |
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- "2023_part_15.jsonl.gz" |
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- config_name: "2024" |
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data_files: |
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- "2024_part_00.jsonl.gz" |
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- "2024_part_01.jsonl.gz" |
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- "2024_part_02.jsonl.gz" |
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- "2024_part_03.jsonl.gz" |
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- "2024_part_04.jsonl.gz" |
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- "2024_part_05.jsonl.gz" |
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- "2024_part_06.jsonl.gz" |
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--- |
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This dataset is the result of processing all WARC files in the [CCNews Corpus](https://commoncrawl.org/blog/news-dataset-available), from the beginning (2016) to June of 2024. |
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The data has been cleaned and deduplicated, and language of articles have been detected and added. The process is similar to what HuggingFace's [DataTrove](https://github.com/huggingface/datatrove) does. |
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Overall, it contains about 600 million news articles in more than 100 languages from all around the globe. |
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Sample Python code to explore this dataset: |
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```python |
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from datasets import load_dataset |
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from tqdm import tqdm |
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# Load the news articles **crawled** in the year 2016 (but not necessarily published in 2016), in streaming mode |
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dataset = load_dataset("stanford-oval/ccnews", name="2016", streaming=True) # `name` can be one of 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024 |
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# Print information about the dataset |
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print(dataset) |
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# Iterate over a few examples |
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print("\nFirst few examples:") |
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for i, example in enumerate(dataset["train"].take(5)): |
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print(f"Example {i + 1}:") |
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print(example) |
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print() |
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|
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# Count the number of articles (in 2016) |
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row_count = 0 |
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for _ in tqdm(dataset["train"], desc="Counting rows", unit=" rows", unit_scale=True, unit_divisor=1000): |
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row_count += 1 |
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# Print the number of rows |
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print(f"\nTotal number of articles: {row_count}") |
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``` |
