Datasets:
Languages:
English
Multilinguality:
monolingual
Size Categories:
1M<n<10M
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. | |
| """The Open WebText Corpus""" | |
| import re | |
| import datasets | |
| _CITATION = """\ | |
| @misc{Gokaslan2019OpenWeb, | |
| title={OpenWebText Corpus}, | |
| author={Aaron Gokaslan*, Vanya Cohen*, Ellie Pavlick, Stefanie Tellex}, | |
| howpublished{\\url{http://Skylion007.github.io/OpenWebTextCorpus}}, | |
| year={2019} | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| An open-source replication of the WebText dataset from OpenAI. | |
| """ | |
| _N_DATA_FILES = 21 | |
| _DATA_FILES = ["subsets/urlsf_subset{:02d}.tar".format(i) for i in range(_N_DATA_FILES)] | |
| class Openwebtext(datasets.GeneratorBasedBuilder): | |
| """The Open WebText dataset.""" | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig( | |
| name="plain_text", | |
| description="Plain text", | |
| version=datasets.Version("1.0.0"), | |
| ) | |
| ] | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features({"text": datasets.Value("string")}), | |
| homepage="https://skylion007.github.io/OpenWebTextCorpus/", | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| archives = dl_manager.download(_DATA_FILES) | |
| return [ | |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={ | |
| "archive_iterators": [ | |
| dl_manager.iter_archive(archive) for archive in archives | |
| ], | |
| "iter_archive": dl_manager.iter_archive | |
| }), | |
| ] | |
| def _generate_examples(self, archive_iterators, iter_archive): | |
| """Yields examples.""" | |
| for archive_iterator in archive_iterators: | |
| for xz_filepath, xz_f in archive_iterator: | |
| if not xz_filepath.endswith(".xz"): | |
| continue | |
| for txt_filepath, txt_f in iter_archive(xz_f): | |
| if not txt_filepath.endswith(".txt"): | |
| continue | |
| idx = f"{xz_filepath}/{txt_filepath}" | |
| yield idx, {"text": re.sub("\n\n\n+", "\n\n", txt_f.read().decode("utf-8")).strip()} | |