Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
webdataset
Languages:
English
Size:
< 1K
Tags:
jira
| """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)} | |