Update files from the datasets library (from 1.3.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.3.0

README.md

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+---
+---
+
+# Dataset Card for "reddit"
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits Sample Size](#data-splits-sample-size)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## [Dataset Description](#dataset-description)
+
+- **Homepage:** [https://github.com/webis-de/webis-tldr-17-corpus](https://github.com/webis-de/webis-tldr-17-corpus)
+- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+- **Size of downloaded dataset files:** 2996.31 MB
+- **Size of the generated dataset:** 18063.11 MB
+- **Total amount of disk used:** 21059.41 MB
+
+### [Dataset Summary](#dataset-summary)
+
+This corpus contains preprocessed posts from the Reddit dataset.
+The dataset consists of 3,848,330 posts with an average length of 270 words for content,
+and 28 words for the summary.
+
+Features includes strings: author, body, normalizedBody, content, summary, subreddit, subreddit_id.
+Content is used as document and summary is used as summary.
+
+### [Supported Tasks](#supported-tasks)
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### [Languages](#languages)
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+## [Dataset Structure](#dataset-structure)
+
+We show detailed information for up to 5 configurations of the dataset.
+
+### [Data Instances](#data-instances)
+
+#### default
+
+- **Size of downloaded dataset files:** 2996.31 MB
+- **Size of the generated dataset:** 18063.11 MB
+- **Total amount of disk used:** 21059.41 MB
+
+An example of 'train' looks as follows.
+```
+{
+    "author": "me",
+    "body": "<>",
+    "content": "input document.",
+    "id": "1",
+    "normalizedBody": "",
+    "subreddit": "machinelearning",
+    "subreddit_id": "2",
+    "summary": "output summary."
+}
+```
+
+### [Data Fields](#data-fields)
+
+The data fields are the same among all splits.
+
+#### default
+- `author`: a `string` feature.
+- `body`: a `string` feature.
+- `normalizedBody`: a `string` feature.
+- `subreddit`: a `string` feature.
+- `subreddit_id`: a `string` feature.
+- `id`: a `string` feature.
+- `content`: a `string` feature.
+- `summary`: a `string` feature.
+
+### [Data Splits Sample Size](#data-splits-sample-size)
+
+| name  | train |
+|-------|------:|
+|default|3848330|
+
+## [Dataset Creation](#dataset-creation)
+
+### [Curation Rationale](#curation-rationale)
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### [Source Data](#source-data)
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### [Annotations](#annotations)
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### [Personal and Sensitive Information](#personal-and-sensitive-information)
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+## [Considerations for Using the Data](#considerations-for-using-the-data)
+
+### [Social Impact of Dataset](#social-impact-of-dataset)
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### [Discussion of Biases](#discussion-of-biases)
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### [Other Known Limitations](#other-known-limitations)
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+## [Additional Information](#additional-information)
+
+### [Dataset Curators](#dataset-curators)
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### [Licensing Information](#licensing-information)
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### [Citation Information](#citation-information)
+
+```
+
+@inproceedings{volske-etal-2017-tl,
+    title = "{TL};{DR}: Mining {R}eddit to Learn Automatic Summarization",
+    author = {V{"o}lske, Michael  and
+      Potthast, Martin  and
+      Syed, Shahbaz  and
+      Stein, Benno},
+    booktitle = "Proceedings of the Workshop on New Frontiers in Summarization",
+    month = sep,
+    year = "2017",
+    address = "Copenhagen, Denmark",
+    publisher = "Association for Computational Linguistics",
+    url = "https://www.aclweb.org/anthology/W17-4508",
+    doi = "10.18653/v1/W17-4508",
+    pages = "59--63",
+    abstract = "Recent advances in automatic text summarization have used deep neural networks to generate high-quality abstractive summaries, but the performance of these models strongly depends on large amounts of suitable training data. We propose a new method for mining social media for author-provided summaries, taking advantage of the common practice of appending a {``}TL;DR{''} to long posts. A case study using a large Reddit crawl yields the Webis-TLDR-17 dataset, complementing existing corpora primarily from the news genre. Our technique is likely applicable to other social media sites and general web crawls.",
+}
+
+```
+
+
+### Contributions
+
+Thanks to [@mariamabarham](https://github.com/mariamabarham), [@patrickvonplaten](https://github.com/patrickvonplaten), [@thomwolf](https://github.com/thomwolf) for adding this dataset.