CoCalc -- dataset

GitHub Repository: amanchadha/coursera-natural-language-processing-specialization
Path: blob/master/4 - Natural Language Processing with Attention Models/Week 2/data/wikihow/all/1.2.0/dataset_info.json
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{
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  "citation": "@misc{koupaee2018wikihow,\n    title={WikiHow: A Large Scale Text Summarization Dataset},\n    author={Mahnaz Koupaee and William Yang Wang},\n    year={2018},\n    eprint={1810.09305},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}",
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  "description": "WikiHow is a new large-scale dataset using the online WikiHow\n(http://www.wikihow.com/) knowledge base.\n\nThere are two features:\n  - text: wikihow answers texts.\n  - headline: bold lines as summary.\n\nThere are two separate versions:\n  - all: consisting of the concatenation of all paragraphs as the articles and\n         the bold lines as the reference summaries.\n  - sep: consisting of each paragraph and its summary.\n\nDownload \"wikihowAll.csv\" and \"wikihowSep.csv\" from\nhttps://github.com/mahnazkoupaee/WikiHow-Dataset and place them in manual folder\nhttps://www.tensorflow.org/datasets/api_docs/python/tfds/download/DownloadConfig.\nTrain/validation/test splits are provided by the authors.\nPreprocessing is applied to remove short articles\n(abstract length < 0.75 article length) and clean up extra commas.",
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  "downloadSize": "5460385",
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  "location": {
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    "urls": [
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      "https://github.com/mahnazkoupaee/WikiHow-Dataset"
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    ]
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  },
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  "name": "wikihow",
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  "schema": {
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    "feature": [
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      {
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        "name": "headline",
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        "type": "BYTES"
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      },
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      {
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        "name": "text",
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        "type": "BYTES"
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      },
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      {
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        "name": "title",
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        "type": "BYTES"
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      }
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      "name": "validation",
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  "supervisedKeys": {
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    "input": "text",
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    "output": "headline"
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  "version": "1.2.0"
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}
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