Datasets:

Heng666
/

Traditional_Chinese-aya_collection

	# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
	#
	# 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.
	# TODO: Address all TODOs and remove all explanatory comments
	"""ted2020_tw_mt"""


	import csv
	import json
	import os
	import datasets


	# TODO: Add BibTeX citation
	# Find for instance the citation on arxiv or on the dataset repo/website
	_CITATION = """\
	@InProceedings{huggingface:dataset,
	title = {中文 Aya collection},
	author={Heng-Shiou Sheu
	},
	year={2024}
	}
	"""

	# You can copy an official description
	_DESCRIPTION = """\
	是一個精心策劃的資料集，源自 CohereForAI 的綜合 Aya 集合，特別關注繁體中文資料。
	此資料集聚合了 CohereForAI/aya_collection、CohereForAI/aya_dataset 和 CohereForAI/aya_evaluation_suite 中的內容，
	過濾掉除中文內容之外的所有內容，包括繁體中文與簡體中文。
	"""

	# TODO 請使用 MAC 讀取資料夾內容來做更新
	_Subset_names = [
	'aya_dataset',
	'templated_ntx_llm',
	'templated_uner_llm',
	'templated_xcsqa',
	'templated_xlel_wd',
	'templated_xwikis',
	'translated_adversarial_qa',
	'translated_cnn_dailymail',
	'translated_dolly',
	'translated_flan_coqa',
	'translated_flan_cot',
	'translated_flan_gem_wiki',
	'translated_flan_lambada',
	'translated_flan_qa',
	'translated_hotpotqa',
	'translated_joke_explaination',
	'translated_mintaka',
	'translated_mlqa',
	'translated_nqopen',
	'translated_paws',
	'translated_piqa',
	'translated_wikiqa'
	]

	# TODO: Add a link to an official homepage for the dataset here
	_HOMEPAGE = "https://huggingface.co/Heng666"

	_LICENSE = "apache-2.0"

	# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
	# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
	_URLS = {
	"aya_collection": "https://huggingface.co/datasets/CohereForAI/aya_collection",
	"aya_dataset": "https://huggingface.co/datasets/CohereForAI/aya_dataset",
	"evaluation_suite": "https://huggingface.co/datasets/CohereForAI/aya_evaluation_suite"
	}

	class ChineseAyaCollectionConfig(datasets.BuilderConfig):
	"""BuilderConfig for Chinese Aya"""

	def __init__(self, subset, **kwargs):
	super().__init__(**kwargs)
	"""
	Args:
	subset: subset, you want to load
	**kwargs: keyword arguments forwarded to super.
	"""
	self.subset = subset


	class ChineseAyaCollectionDataset(datasets.GeneratorBasedBuilder):
	"""TODO: Short description of my dataset."""

	VERSION = datasets.Version("1.0.0")

	BUILDER_CONFIG_CLASS = ChineseAyaCollectionConfig

	BUILDER_CONFIGS = [
	ChineseAyaCollectionConfig(
	name=subset,
	description=_DESCRIPTION,
	subset=subset
	)
	for subset in _Subset_names
	]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features({
	"id": datasets.Value("int64"),
	"inputs": datasets.Value("string"),
	"targets": datasets.Value("string"),
	"dataset_name": datasets.Value("string"),
	"sub_dataset_name": datasets.Value("string"),
	"task_type": datasets.Value("string"),
	"template_id": datasets.Value("string"),
	"language_code": datasets.Value("string"),
	"split": datasets.Value("string"),
	"script": datasets.Value("string"),
	}),
	homepage=_HOMEPAGE,
	citation=_CITATION,
	license=_LICENSE
	)

	def _split_generators(self, dl_manager):

	subset = self.config.subset

	files = {}

	train_path = os.path.join("train/", f"CohereForAI-{subset}-train.csv")
	files["train"] = train_path
	test_path = os.path.join("test", f"CohereForAI-{subset}-test.csv")
	files["test"] = test_path
	validation_path = os.path.join("validation", f"CohereForAI-{subset}-validation.csv")
	files["validation"] = validation_path

	try:
	data_dir = dl_manager.download_and_extract(files)
	except:
	files.pop("test")
	files.pop("validation")
	data_dir = dl_manager.download_and_extract(files)

	output = []
	if "train" in files:
	train = datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"filepath": data_dir["train"]
	}
	)
	output.append(train)

	if "test" in files:
	test = datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"filepath": data_dir["test"]
	}
	)
	output.append(test)

	if "validation" in files:
	validation = datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={
	"filepath": data_dir["validation"]
	}
	)
	output.append(validation)

	return output

	# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
	def _generate_examples(self, filepath):
	"""Yields examples."""
	with open(filepath, encoding="utf-8") as f:
	reader = csv.reader(f, delimiter=",", quotechar='"')
	for id_, row in enumerate(reader):
	if id_ == 0:
	continue
	yield id_, {
	"id": row[0],
	"inputs": row[1],
	"targets": row[2],
	"dataset_name": row[3],
	"sub_dataset_name": row[4],
	"task_type": row[5],
	"template_id": row[6],
	"language_code": row[7],
	"split": row[8],
	"script": row[9],
	}