"""Cleaned dataset for Swahili Language Modeling""" import datasets _CITATION = """\ @InProceedings{huggingface:flax-community, title = Cleaned dataset for Swahili Language Modeling, authors={Fitsum, Alok, Patrick}, year={2021}, link = https://huggingface.co/datasets/flax-community/swahili-safi } """ _DESCRIPTION = """Cleaned dataset for Swahili Language Modeling""" _HOMEPAGE = "https://huggingface.co/datasets/flax-community/swahili-safi" _LICENSE = "Attribution 4.0 International" _REPO_URL = "https://huggingface.co/datasets/flax-community/swahili-safi/resolve/main/" _TRAIN= [_REPO_URL + file_name for file_name in [ "data/train.txt", ]] class SwahiliSafi(datasets.GeneratorBasedBuilder): """The Swahili dataset for language modeling""" VERSION = datasets.Version("1.0.0") BUILDER_CONFIGS = [ datasets.BuilderConfig( name="swahili-safi", version=VERSION, description="Language modeling dataset for Swahili" ), ] def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "text": datasets.Value("string"), } ), supervised_keys=None, homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION, ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" train_files = dl_manager.download(_TRAIN) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "data_files": train_files, "split": "train", }, ) ] def _generate_examples(self, data_files, split): """Yields examples.""" _id = 0 for filepath in data_files: with open(filepath, mode="r", encoding="utf-8") as f: for line in f: yield _id, {"text": line.strip()}, _id += 1