Datasets:
Languages:
Sanskrit
Multilinguality:
monolingual
Size Categories:
100K<n<1M
Language Creators:
found
Annotations Creators:
no-annotation
Source Datasets:
original
Tags:
License:
| # coding=utf-8 | |
| # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| """TODO: Add a description here.""" | |
| import os | |
| import datasets | |
| _CITATION = """\ | |
| @Misc{johnsonetal2014, | |
| author = {Johnson, Kyle P. and Patrick Burns and John Stewart and Todd Cook}, | |
| title = {CLTK: The Classical Language Toolkit}, | |
| url = {https://github.com/cltk/cltk}, | |
| year = {2014--2020}, | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| This dataset combines some of the classical Sanskrit texts. | |
| """ | |
| _HOMEPAGE = "https://github.com/parmarsuraj99/hf_datasets/tree/master/sanskrit_classic" | |
| _LICENSE = "" | |
| _URLs = { | |
| "combined": "https://github.com/parmarsuraj99/hf_datasets/raw/master/sanskrit_classic/combined.zip", | |
| } | |
| class SanskritClassic(datasets.GeneratorBasedBuilder): | |
| """TODO: Short description of my dataset.""" | |
| VERSION = datasets.Version("1.1.0") | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig( | |
| name="combined", version=VERSION, description="This is combined version of classical texts" | |
| ), | |
| ] | |
| def _info(self): | |
| features = datasets.Features( | |
| { | |
| "text": datasets.Value("string"), | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| supervised_keys=None, | |
| homepage=_HOMEPAGE, | |
| license=_LICENSE, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| """Returns SplitGenerators.""" | |
| my_urls = _URLs[self.config.name] | |
| data_dir = dl_manager.download_and_extract(my_urls) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| # These kwargs will be passed to _generate_examples | |
| gen_kwargs={ | |
| "filepath": os.path.join(data_dir, "combined.txt"), | |
| "split": "train", | |
| }, | |
| ), | |
| ] | |
| def _generate_examples(self, filepath, split): | |
| """Yields examples.""" | |
| with open(filepath, encoding="utf-8") as f: | |
| for id_, row in enumerate(f): | |
| yield id_, { | |
| "text": row, | |
| } | |