Datasets:
Tasks:
Multiple Choice
Sub-tasks:
multiple-choice-qa
Languages:
English
Size:
10K<n<100K
ArXiv:
License:
Update files from the datasets library (from 1.2.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.2.0
- cosmos_qa.py +7 -9
cosmos_qa.py
CHANGED
@@ -4,7 +4,6 @@ from __future__ import absolute_import, division, print_function
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import csv
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import json
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import os
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import datasets
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@@ -24,10 +23,13 @@ _CITATION = """\
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_DESCRIPTION = """\
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Cosmos QA is a large-scale dataset of 35.6K problems that require commonsense-based reading comprehension, formulated as multiple-choice questions. It focuses on reading between the lines over a diverse collection of people's everyday narratives, asking questions concerning on the likely causes or effects of events that require reasoning beyond the exact text spans in the context
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"""
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_URL = "https://github.com/wilburOne/cosmosqa/raw/master/data/"
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class CosmosQa(datasets.GeneratorBasedBuilder):
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@@ -69,11 +71,7 @@ class CosmosQa(datasets.GeneratorBasedBuilder):
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# TODO(cosmos_qa): Downloads the data and defines the splits
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# dl_manager is a datasets.download.DownloadManager that can be used to
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# download and extract URLs
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urls_to_download =
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"train": os.path.join(_URL, _TRAIN_FILE),
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"test": os.path.join(_URL, _TEST_FILE),
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"dev": os.path.join(_URL, _DEV_FILE),
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}
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dl_dir = dl_manager.download_and_extract(urls_to_download)
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return [
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datasets.SplitGenerator(
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import csv
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import json
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import datasets
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_DESCRIPTION = """\
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Cosmos QA is a large-scale dataset of 35.6K problems that require commonsense-based reading comprehension, formulated as multiple-choice questions. It focuses on reading between the lines over a diverse collection of people's everyday narratives, asking questions concerning on the likely causes or effects of events that require reasoning beyond the exact text spans in the context
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"""
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+
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_URL = "https://github.com/wilburOne/cosmosqa/raw/master/data/"
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_URLS = {
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"train": _URL + "train.csv",
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"test": _URL + "test.jsonl",
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"dev": _URL + "valid.csv",
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}
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class CosmosQa(datasets.GeneratorBasedBuilder):
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# TODO(cosmos_qa): Downloads the data and defines the splits
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# dl_manager is a datasets.download.DownloadManager that can be used to
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# download and extract URLs
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urls_to_download = _URLS
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dl_dir = dl_manager.download_and_extract(urls_to_download)
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return [
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datasets.SplitGenerator(
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