File size: 2,155 Bytes
f1f6712 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 |
"""Maroon Indonesian 100k Summarization Dataset."""
import json
import os
import datasets
_DESCRIPTION = """\
Combine IndoSum + Liputan6 in 100k rows.
"""
_URL = "https://huggingface.co/datasets/bgspaditya/maroon100k/blob/main/maroondata.tar.bz2"
class Maroon100k(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("2.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name="Maroon100k",
version=datasets.Version("2.0.0")
)
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"article": datasets.Value("string"),
"summary": datasets.Value("string"),
}
),
supervised_keys=None,
# citation=_CITATION,
# license=_LICENSE,
version=self.VERSION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
url = _URL
data_dir = dl_manager.download_and_extract(url)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": os.path.join(data_dir, "train.jsonl"),
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"filepath": os.path.join(data_dir, "test.jsonl"),
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"filepath": os.path.join(data_dir, "valid.jsonl"),
},
),
]
def _generate_examples(self, filepath):
"""Yields examples as (key, example) tuples."""
with open(filepath, encoding="utf-8") as f:
for idx_, row in enumerate(f):
data = json.loads(row)
yield idx_, {
"article": data["article"],
"summary": data["summary"],
} |