Datasets:
Tasks:
Text Retrieval
Modalities:
Text
Sub-tasks:
document-retrieval
Size:
10M - 100M
ArXiv:
License:
File size: 3,154 Bytes
a7362f0 d0e7410 a7362f0 262aa62 a7362f0 322e02f a7362f0 |
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 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 |
# coding=utf-8
# 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.
# Lint as: python3
import json
import datasets
from dataclasses import dataclass
_CITATION = '''
'''
languages2filesize = {
'ar': 5,
'bn': 1,
'en': 66 ,
'es': 21,
'fa': 5,
'fi': 4,
'fr': 30,
'hi': 2,
'id': 3,
'ja': 14,
'ko': 3,
'ru': 20,
'sw': 1,
'te': 2,
'th': 2,
'zh': 10,
'de': 32,
'yo': 1,
}
_DESCRIPTION = 'dataset load script for MIRACL'
_DATASET_URLS = {
lang: {
'train': [
f'https://huggingface.co/datasets/miracl/miracl-corpus/resolve/main/miracl-corpus-v1.0-{lang}/docs-{i}.jsonl.gz' for i in range(n)
]
} for lang, n in languages2filesize.items()
}
class MIRACLCorpus(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
datasets.BuilderConfig(
version=datasets.Version('1.0.0'),
name=lang,
description=f'MIRACL dataset in language {lang}.'
) for lang in languages2filesize
]
def _info(self):
features = datasets.Features({
'docid': datasets.Value('string'),
'title': datasets.Value('string'),
'text': datasets.Value('string'),
})
return datasets.DatasetInfo(
# This is the description that will appear on the datasets page.
description=_DESCRIPTION,
# This defines the different columns of the dataset and their types
features=features, # Here we define them above because they are different between the two configurations
supervised_keys=None,
# Homepage of the dataset for documentation
homepage='https://project-miracl.github.io',
# License for the dataset if available
license='',
# Citation for the dataset
citation=_CITATION,
)
def _split_generators(self, dl_manager):
lang = self.config.name
downloaded_files = dl_manager.download_and_extract(_DATASET_URLS[lang])
splits = [
datasets.SplitGenerator(
name='train',
gen_kwargs={
'filepaths': downloaded_files['train'],
},
),
]
return splits
def _generate_examples(self, filepaths):
for filepath in sorted(filepaths):
with open(filepath, encoding="utf-8") as f:
for line in f:
data = json.loads(line)
yield data['docid'], data
|