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Dataset: reddit 🏷
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How to load this dataset directly with the πŸ€—/nlp library:

			
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from nlp import load_dataset dataset = load_dataset("reddit")

Description

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.

Citation

@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.},
}

Models trained or fine-tuned on reddit

None yet. Start fine-tuning now =)