[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2022-12-06 UTC."],[],[],null,["# xsum\n\n\u003cbr /\u003e\n\n| **Warning:** Manual download required. See instructions below.\n\n- **Description**:\n\nExtreme Summarization (XSum) Dataset.\n\nThere are two features: - document: Input news article. - summary: One sentence\nsummary of the article.\n\nThis data need to manaully downloaded and extracted as described in\n\u003chttps://github.com/EdinburghNLP/XSum/blob/master/XSum-Dataset/README.md\u003e The\nfolder 'xsum-extracts-from-downloads' need to be compressed as\n'xsum-extracts-from-downloads.tar.gz' and put in manually downloaded folder.\n\n- **Additional Documentation** :\n [Explore on Papers With Code\n north_east](https://paperswithcode.com/dataset/xsum)\n\n- **Homepage** :\n \u003chttps://github.com/EdinburghNLP/XSum/tree/master/XSum-Dataset\u003e\n\n- **Source code** :\n [`tfds.summarization.Xsum`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/summarization/xsum.py)\n\n- **Versions**:\n\n - `1.0.0`: Dataset without cleaning.\n - **`1.1.0`** (default): Removes web contents.\n- **Download size** : `2.59 MiB`\n\n- **Dataset size** : `512.03 MiB`\n\n- **Manual download instructions** : This dataset requires you to\n download the source data manually into `download_config.manual_dir`\n (defaults to `~/tensorflow_datasets/downloads/manual/`): \n\n Detailed download instructions (which require running a custom script) are\n here:\n \u003chttps://github.com/EdinburghNLP/XSum/blob/master/XSum-Dataset/README.md#running-the-download-and-extraction-scripts\u003e\n Afterwards, please put xsum-extracts-from-downloads.tar.gz file in the manual_dir.\n\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n No\n\n- **Splits**:\n\n| Split | Examples |\n|----------------|----------|\n| `'test'` | 11,301 |\n| `'train'` | 203,577 |\n| `'validation'` | 11,305 |\n\n- **Feature structure**:\n\n FeaturesDict({\n 'document': Text(shape=(), dtype=string),\n 'summary': Text(shape=(), dtype=string),\n })\n\n- **Feature documentation**:\n\n| Feature | Class | Shape | Dtype | Description |\n|----------|--------------|-------|--------|-------------|\n| | FeaturesDict | | | |\n| document | Text | | string | |\n| summary | Text | | string | |\n\n- **Supervised keys** (See\n [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):\n `('document', 'summary')`\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n Not supported.\n\n- **Examples**\n ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\n- **Citation**:\n\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 }"]]