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README.md

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+# reddit first 450000 dataset

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dataset_info.json

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+{
+  "builder_name": "tldr-17",
+  "citation": "\n@inproceedings{volske-etal-2017-tl,\n    title = {TL;DR: Mining {R}eddit to Learn Automatic Summarization},\n    author = {V{\"o}lske, Michael  and Potthast, Martin  and Syed, Shahbaz  and Stein, Benno},\n    booktitle = {Proceedings of the Workshop on New Frontiers in Summarization},\n    month = {sep},\n    year = {2017},\n    address = {Copenhagen, Denmark},\n    publisher = {Association for Computational Linguistics},\n    url = {https://www.aclweb.org/anthology/W17-4508},\n    doi = {10.18653/v1/W17-4508},\n    pages = {59--63},\n    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.},\n}\n",
+  "config_name": "default",
+  "dataset_name": "tldr-17",
+  "dataset_size": 18936201253,
+  "description": "\nThis corpus contains preprocessed posts from the Reddit dataset.\nThe dataset consists of 3,848,330 posts with an average length of 270 words for content,\nand 28 words for the summary.\n\nFeatures includes strings: author, body, normalizedBody, content, summary, subreddit, subreddit_id.\nContent is used as document and summary is used as summary.\n",
+  "download_checksums": {
+    "data/corpus-webis-tldr-17.zip": {
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+      "checksum": null
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+  },
+  "download_size": 3141854161,
+  "features": {
+    "author": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "body": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "normalizedBody": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "subreddit": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "subreddit_id": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "id": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "content": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "summary": {
+      "dtype": "string",
+      "_type": "Value"
+    }
+  },
+  "homepage": "https://github.com/webis-de/webis-tldr-17-corpus",
+  "license": "",
+  "size_in_bytes": 22078055414,
+  "splits": {
+    "train": {
+      "name": "train",
+      "num_bytes": 18936201253,
+      "num_examples": 3848330,
+      "shard_lengths": [
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+      "dataset_name": "tldr-17"
+    }
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+  "version": {
+    "version_str": "1.0.0",
+    "major": 1,
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+    "patch": 0
+  }
+}

state.json

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+  "_fingerprint": "d80a3a13d3bc18f0",
+  "_format_columns": null,
+  "_format_kwargs": {},
+  "_format_type": null,
+  "_output_all_columns": false,
+  "_split": "train[:450000]"
+}