Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
webdataset
Languages:
English
Size:
< 1K
Tags:
jira
File size: 2,069 Bytes
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"""The BookCorpus dataset."""
import datasets
import os
import json
_DESCRIPTION = """\
Dataset of jira comments from different projects of Apache and more.
"""
_CITATION = """\
@InProceedings{Zhu_2015_ICCV,
title = {Jira commentaries},
author = {Filipp Abapolov},
month = {Fubruary},
year = {2023}
}
"""
_REPO = "https://huggingface.co/datasets/pheepa/jira-comments/resolve/main"
_URL = f"{_REPO}/data/jira-comments.tar.gz"
class JiraComments(datasets.GeneratorBasedBuilder):
"""JiraComments dataset."""
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name='jira-comments',
version=datasets.Version("1.0.0"),
description=_DESCRIPTION
)
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"sentence_a": datasets.Value("string"),
"sentence_b": datasets.Value("string"),
"next_sentence_label": datasets.Value("int32")
}
),
supervised_keys=None,
citation=_CITATION
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
data_dir = dl_manager.download_and_extract(_URL)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"filepath": os.path.join(data_dir, "train-pairs-jira-comments.txt")}
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"filepath": os.path.join(data_dir, "test-pairs-jira-comments.txt")}
)
]
def _generate_examples(self, filepath):
"""Yields examples."""
with open(filepath, 'r') as f:
triples = f.read().split('\n')
for i in range(0, len(triples) - 1, 3):
l, a, b = triples[i:i+3]
yield i // 3, {"sentence_a": a, 'sentence_b': b, 'next_sentence_label': int(l)}
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