Datasets:
Tasks:
Text Retrieval
Multilinguality:
multilingual
Size Categories:
1M<n<10M
Language Creators:
machine-generated
Annotations Creators:
machine-generated
Source Datasets:
extended|irds/msmarco-passage
Tags:
| import tarfile | |
| import os | |
| import datasets | |
| _URLS = { | |
| "neumarco": "https://huggingface.co/datasets/neuclir/neumarco/resolve/main/data/neumarco.tar.gz" | |
| } | |
| class Neumarco(datasets.GeneratorBasedBuilder): | |
| VERSION = datasets.Version("1.0.0") | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| features=datasets.Features({ | |
| "doc_id": datasets.Value("string"), | |
| "text": datasets.Value("string"), | |
| }), | |
| ) | |
| def _split_generators(self, dl_manager): | |
| paths = dl_manager.download(_URLS) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=lang, | |
| gen_kwargs={ | |
| "filepath": paths['neumarco'], | |
| "tarpath": f'eng-{lang}/msmarco.collection.20210731-scale21-sockeye2-tm1.tsv' | |
| }) | |
| for lang in ['fas', 'rus', 'zho'] | |
| ] | |
| def _generate_examples(self, filepath, tarpath): | |
| with tarfile.open(filepath, 'r|gz') as tarf: | |
| for fileinfo in tarf: | |
| if fileinfo.name != tarpath: | |
| continue | |
| with tarf.extractfile(fileinfo) as f: | |
| for key, line in enumerate(f): | |
| doc_id, text = line.decode('utf8').rstrip('\n').split('\t') | |
| yield key, {'doc_id': doc_id, 'text': text} | |
| break | |