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import csv
import datasets
class Finstsb(datasets.GeneratorBasedBuilder):
"""Finstsb dataset."""
VERSION = datasets.Version("1.0.0")
def _info(self):
return datasets.DatasetInfo(
description="Finstsb dataset",
features=datasets.Features(
{
"sentence1": datasets.Value("string"),
"sentence2": datasets.Value("string"),
"gpt_score": datasets.Value("int32"),
"score": datasets.Value("int32"),
}
),
supervised_keys=None,
homepage="https://huggingface.co/datasets",
citation="",
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
urls_to_download = {
"dev": "path/to/your/finstsb_to_dev.csv",
"test": "path/to/your/finstsb_to_test.csv",
}
downloaded_files = dl_manager.download_and_extract(urls_to_download)
return [
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"filepath": downloaded_files["dev"]},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"filepath": downloaded_files["test"]},
),
]
def _generate_examples(self, filepath):
"""Yields examples."""
with open(filepath, encoding="utf-8") as f:
reader = csv.DictReader(f)
for id_, row in enumerate(reader):
yield id_, {
"sentence1": row["sentence1"],
"sentence2": row["sentence2"],
"gpt_score": int(row["gpt_score"]),
"score": int(row["score"]),
}
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