Datasets:
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import json
import datasets
_DESCRIPTION = """\
This dataset determines whether a GitHub repository description relates to Japanese natural language processing (NLP). The labels are categorized as "Relevant (1)" and "Not Relevant (0)".
"""
_HOMEPAGE = "https://github.com/taishi-i/awesome-japanese-nlp-resources"
_CITATION = ""
_LICENSE = "other"
class NagisaStopwordsDataset(datasets.GeneratorBasedBuilder):
"""awesome-japanese-nlp-classification-dataset."""
VERSION = datasets.Version("0.0.1")
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name="awesome-japanese-nlp-classification-dataset",
version=VERSION,
description=_DESCRIPTION,
),
]
def _info(self):
features = datasets.Features(
{
"label": datasets.features.ClassLabel(names=["0", "1"]),
"text": datasets.Value("string"),
"url": datasets.Value("string"),
"created_at": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
data_url = "https://huggingface.co/datasets/taishi-i/awesome-japanese-nlp-classification-dataset/raw/main"
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": dl_manager.download_and_extract(
f"{data_url}/train.json"
),
"split": "train",
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"filepath": dl_manager.download_and_extract(
f"{data_url}/val.json"
),
"split": "val",
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"filepath": dl_manager.download_and_extract(
f"{data_url}/test.json"
),
"split": "test",
},
),
]
def _generate_examples(self, filepath, split):
"""Generates examples."""
with open(filepath, "r") as file:
data = json.load(file)
for id_, row in enumerate(data):
yield id_, {
"label": row["label"],
"text": row["text"],
"url": row["url"],
"created_at": row["created_at"],
}
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