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import datasets |
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_DESCRIPTION = """\ |
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This corpus is an attempt to recreate the dataset used for training XLM-R. This corpus comprises of monolingual data for 100+ languages and also includes data for romanized languages (indicated by *_rom). This was constructed using the urls and paragraph indices provided by the CC-Net repository by processing January-December 2018 Commoncrawl snapshots. Each file comprises of documents separated by double-newlines and paragraphs within the same document separated by a newline. The data is generated using the open source CC-Net repository. No claims of intellectual property are made on the work of preparation of the corpus. |
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""" |
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_HOMEPAGE_URL = "https://data.statmt.org/cc-100/" |
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_CITATION = """\ |
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@inproceedings{conneau-etal-2020-unsupervised, |
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title = "Unsupervised Cross-lingual Representation Learning at Scale", |
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author = "Conneau, Alexis and |
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Khandelwal, Kartikay and |
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Goyal, Naman and |
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Chaudhary, Vishrav and |
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Wenzek, Guillaume and |
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Guzm{\\'a}n, Francisco and |
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Grave, Edouard and |
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Ott, Myle and |
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Zettlemoyer, Luke and |
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Stoyanov, Veselin", |
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editor = "Jurafsky, Dan and |
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Chai, Joyce and |
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Schluter, Natalie and |
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Tetreault, Joel", |
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booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics", |
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month = jul, |
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year = "2020", |
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address = "Online", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2020.acl-main.747", |
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doi = "10.18653/v1/2020.acl-main.747", |
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pages = "8440--8451", |
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} |
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@inproceedings{wenzek-etal-2020-ccnet, |
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title = "{CCN}et: Extracting High Quality Monolingual Datasets from Web Crawl Data", |
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author = "Wenzek, Guillaume and |
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Lachaux, Marie-Anne and |
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Conneau, Alexis and |
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Chaudhary, Vishrav and |
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Guzm{\\'a}n, Francisco and |
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Joulin, Armand and |
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Grave, Edouard", |
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editor = "Calzolari, Nicoletta and |
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B{\\'e}chet, Fr{\\'e}d{\\'e}ric and |
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Blache, Philippe and |
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Choukri, Khalid and |
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Cieri, Christopher and |
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Declerck, Thierry and |
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Goggi, Sara and |
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Isahara, Hitoshi and |
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Maegaard, Bente and |
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Mariani, Joseph and |
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Mazo, H{\\'e}l{\\`e}ne and |
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Moreno, Asuncion and |
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Odijk, Jan and |
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Piperidis, Stelios", |
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booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference", |
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month = may, |
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year = "2020", |
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address = "Marseille, France", |
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publisher = "European Language Resources Association", |
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url = "https://aclanthology.org/2020.lrec-1.494", |
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pages = "4003--4012", |
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language = "English", |
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ISBN = "979-10-95546-34-4", |
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} |
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""" |
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_VERSION = "1.0.0" |
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_BASE_URL = "https://data.statmt.org/cc-100/{}.txt.xz" |
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_LANGUAGES = [ |
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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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"bn_rom", |
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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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"ff", |
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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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"gn", |
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"gu", |
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"ha", |
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"he", |
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"hi", |
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"hi_rom", |
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"hr", |
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"ht", |
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"hu", |
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"hy", |
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"id", |
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"ig", |
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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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"lg", |
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"li", |
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"ln", |
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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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"my_zaw", |
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"ne", |
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"nl", |
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"no", |
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"ns", |
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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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"qu", |
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"rm", |
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"ro", |
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"ru", |
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"sa", |
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"sc", |
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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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"ss", |
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"su", |
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"sv", |
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"sw", |
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"ta", |
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"ta_rom", |
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"te", |
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"te_rom", |
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"th", |
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"tl", |
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"tn", |
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"tr", |
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"ug", |
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"uk", |
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"ur", |
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"ur_rom", |
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"uz", |
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"vi", |
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"wo", |
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"xh", |
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"yi", |
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"yo", |
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"zh-Hans", |
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"zh-Hant", |
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"zu", |
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] |
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class Cc100Config(datasets.BuilderConfig): |
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def __init__(self, *args, lang=None, **kwargs): |
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super().__init__( |
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*args, |
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name=f"{lang}", |
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**kwargs, |
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) |
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self.lang = lang |
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class Cc100(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [ |
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Cc100Config( |
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lang=lang, |
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description=f"Language: {lang}", |
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version=datasets.Version(_VERSION), |
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) |
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for lang in _LANGUAGES |
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] |
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BUILDER_CONFIG_CLASS = Cc100Config |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"id": datasets.Value("string"), |
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"text": datasets.Value("string"), |
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}, |
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), |
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supervised_keys=None, |
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homepage=_HOMEPAGE_URL, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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def _base_url(lang): |
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return _BASE_URL.format(lang) |
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download_url = _base_url(self.config.lang) |
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path = dl_manager.download_and_extract(download_url) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={"datapath": path}, |
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) |
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] |
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def _generate_examples(self, datapath): |
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with open(datapath, encoding="utf-8") as f: |
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for sentence_counter, row in enumerate(f): |
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result = ( |
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sentence_counter, |
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{ |
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"id": str(sentence_counter), |
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"text": row, |
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}, |
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) |
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yield result |
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