Datasets:
Tasks:
Summarization
Modalities:
Text
Sub-tasks:
news-articles-summarization
Languages:
English
Size:
100K - 1M
ArXiv:
License:
Upload data (#3)
Browse files- Upload data (5b1805b1bc7ec93a1a03e5a81d80142b3b931a4e)
- Delete dataset_infos.json (c3b0cf7c3f49c3da12d6720ca367168a31eea9ae)
- Update xsum.py (bd6600fc98a20617d430176179956f8780895873)
- data/XSUM-EMNLP18-Summary-Data-Original.tar.gz +3 -0
- dataset_infos.json +0 -1
- xsum.py +1 -1
data/XSUM-EMNLP18-Summary-Data-Original.tar.gz
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version https://git-lfs.github.com/spec/v1
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oid sha256:10b48aa187fc9c904b30f76ca97e2da0de8d3a1238acc26acadef93e2001af90
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size 254582292
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dataset_infos.json
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{"default": {"description": "\nExtreme Summarization (XSum) Dataset.\n\nThere are three features:\n - document: Input news article.\n - summary: One sentence summary of the article.\n - id: BBC ID of the article.\n\n", "citation": "\n@article{Narayan2018DontGM,\n title={Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization},\n author={Shashi Narayan and Shay B. Cohen and Mirella Lapata},\n journal={ArXiv},\n year={2018},\n volume={abs/1808.08745}\n}\n", "homepage": "https://github.com/EdinburghNLP/XSum/tree/master/XSum-Dataset", "license": "", "features": {"document": {"dtype": "string", "id": null, "_type": "Value"}, "summary": {"dtype": "string", "id": null, "_type": "Value"}, "id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "document", "output": "summary"}, "builder_name": "xsum", "config_name": "default", "version": {"version_str": "1.2.0", "description": null, "major": 1, "minor": 2, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 479206608, "num_examples": 204045, "dataset_name": "xsum"}, "validation": {"name": "validation", "num_bytes": 26292901, "num_examples": 11332, "dataset_name": "xsum"}, "test": {"name": "test", "num_bytes": 26756165, "num_examples": 11334, "dataset_name": "xsum"}}, "download_checksums": {"http://bollin.inf.ed.ac.uk/public/direct/XSUM-EMNLP18-Summary-Data-Original.tar.gz": {"num_bytes": 254582292, "checksum": "10b48aa187fc9c904b30f76ca97e2da0de8d3a1238acc26acadef93e2001af90"}, "https://raw.githubusercontent.com/EdinburghNLP/XSum/master/XSum-Dataset/XSum-TRAINING-DEV-TEST-SPLIT-90-5-5.json": {"num_bytes": 2720574, "checksum": "9c0c5d8f048a90bd68b19a34e4c30577ed270d3247b2119fa06a04ef46292068"}}, "download_size": 257302866, "post_processing_size": null, "dataset_size": 532255674, "size_in_bytes": 789558540}}
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xsum.py
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@@ -44,7 +44,7 @@ There are three features:
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"""
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# From https://github.com/EdinburghNLP/XSum/issues/12
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_URL_DATA = "
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_URL_SPLITS = (
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"https://raw.githubusercontent.com/EdinburghNLP/XSum/master/XSum-Dataset/XSum-TRAINING-DEV-TEST-SPLIT-90-5-5.json"
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)
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"""
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# From https://github.com/EdinburghNLP/XSum/issues/12
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_URL_DATA = "data/XSUM-EMNLP18-Summary-Data-Original.tar.gz"
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_URL_SPLITS = (
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"https://raw.githubusercontent.com/EdinburghNLP/XSum/master/XSum-Dataset/XSum-TRAINING-DEV-TEST-SPLIT-90-5-5.json"
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)
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