Datasets:
Tasks:
Text Generation
Modalities:
Text
Sub-tasks:
language-modeling
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
question-generation
License:
File size: 2,483 Bytes
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import json
import datasets
logger = datasets.logging.get_logger(__name__)
_VERSION = "2.0.1"
_NAME = "qag_tweetqa"
_CITATION = """
TBA
"""
_DESCRIPTION = """Question & answer generation dataset based on [TweetQA](https://huggingface.co/datasets/tweet_qa)."""
_URL = "https://huggingface.co/datasets/lmqg/qag_tweetqa/resolve/main/data/processed"
_URLS = {
'train': f'{_URL}/train.jsonl',
'test': f'{_URL}/test.jsonl',
'validation': f'{_URL}/validation.jsonl'
}
class QAGTweetQAConfig(datasets.BuilderConfig):
"""BuilderConfig"""
def __init__(self, **kwargs):
"""BuilderConfig.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(QAGTweetQAConfig, self).__init__(**kwargs)
class QAGTweetQA(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
QAGTweetQAConfig(name=_NAME, version=datasets.Version(_VERSION), description=_DESCRIPTION),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"answers": datasets.Sequence(datasets.Value("string")),
"questions": datasets.Sequence(datasets.Value("string")),
"paragraph": datasets.Value("string"),
"paragraph_id": datasets.Value("string"),
"questions_answers": datasets.Value("string")
}
),
supervised_keys=None,
homepage="https://github.com/asahi417/lm-question-generation"
)
def _split_generators(self, dl_manager):
downloaded_file = dl_manager.download_and_extract(_URLS)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file["train"]}),
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_file["validation"]}),
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_file["test"]}),
]
def _generate_examples(self, filepath):
_key = 0
logger.info("generating examples from = %s", filepath)
with open(filepath, encoding="utf-8") as f:
_list = f.read().split('\n')
if _list[-1] == '':
_list = _list[:-1]
for i in _list:
data = json.loads(i)
yield _key, data
_key += 1 |