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import datasets |
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_CITATION = """\ |
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@InProceedings{huggingface:dataset, |
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title = {A great new dataset}, |
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author={huggingface, Inc. |
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}, |
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year={2021} |
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} |
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""" |
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_DESCRIPTION = """\ |
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This is a dataset put together to pretrain a language model in Dhivehi, the language of Maldives. |
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""" |
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_HOMEPAGE = "https://huggingface.co/datasets/ashraq/dhivehi-corpus" |
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_LICENSE = "" |
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TRAIN_URL = "train.txt" |
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class DhivehiCorpus(datasets.GeneratorBasedBuilder): |
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VERSION = datasets.Version("1.1.0") |
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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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"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, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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train_path = dl_manager.download_and_extract(TRAIN_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={ |
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"filepath": train_path, |
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"split": "train", |
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}, |
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), |
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] |
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def _generate_examples(self, filepath, split): |
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with open(filepath, encoding="utf8") as f: |
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data = f.readlines() |
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for id_, row in enumerate(data): |
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yield id_, {"text": row.strip()} |
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