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llm-book
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jawiki-paragraphs

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Japanese
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jawiki-paragraphs / jawiki-paragraphs.py
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# Copyright 2020 The HuggingFace Datasets Authors.
# Copyright 2023 Masatoshi Suzuki (@singletongue).
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import io
from typing import Iterator, List, Tuple
import datasets
import pyarrow as pa
_DESCRIPTION = (
"書籍『大規模言語モデル入門』で使用する Wikipedia 段落のデータセットです。"
"GitHub リポジトリ singletongue/wikipedia-utils で公開されているデータセットを利用しています。"
)
_HOMEPAGE = "https://github.com/singletongue/wikipedia-utils"
_LICENSE = (
"本データセットで使用している Wikipedia のコンテンツは、クリエイティブ・コモンズ表示・継承ライセンス 3.0 (CC BY-SA 3.0) "
"および GNU 自由文書ライセンス (GFDL) の下に配布されているものです。"
)
_URL = "https://github.com/singletongue/wikipedia-utils/releases/download/2023-04-03/paragraphs-jawiki-20230403.json.gz"
class JaWikiParagraphs(datasets.ArrowBasedBuilder):
VERSION = datasets.Version("1.0.0")
def _info(self) -> datasets.DatasetInfo:
features = datasets.Features({
"id": datasets.Value("string"),
"pageid": datasets.Value("int64"),
"revid": datasets.Value("int64"),
"paragraph_index": datasets.Value("int64"),
"title": datasets.Value("string"),
"section": datasets.Value("string"),
"text": datasets.Value("string"),
"html_tag": datasets.Value("string"),
})
return datasets.DatasetInfo(
description=_DESCRIPTION,
homepage=_HOMEPAGE,
license=_LICENSE,
features=features,
)
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
filepath = dl_manager.download_and_extract(_URL)
return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": filepath})]
def _generate_tables(self, filepath: str, chunksize: int = 10 << 20) -> Iterator[Tuple[int, pa.Table]]:
# cf. https://github.com/huggingface/datasets/blob/2.12.0/src/datasets/packaged_modules/json/json.py
with open(filepath, "rb") as f:
batch_idx = 0
block_size = max(chunksize // 32, 16 << 10)
while True:
batch = f.read(chunksize)
if not batch:
break
batch += f.readline()
pa_table = pa.json.read_json(
io.BytesIO(batch), read_options=pa.json.ReadOptions(block_size=block_size)
)
yield batch_idx, pa_table
batch_idx += 1