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The Pile™

The Pile is (going to be) the world's largest open source language modeling data set. We are currently developing Version 1, with a goal of 1 TiB of English text.

Component Size Weight Epochs (@1.2TB)
Bibliotik 100.96 GiB 47.48% 5.256
OpenWebText 37.03 GiB 17.41% 5.256
Wikipedia (en) 17.27 GiB 8.12% 5.256
OpenSubtitles 12.98 GiB 6.11% 5.256
Gutenberg (PG-19) 10.88 GiB 5.12% 5.256
Literotica 8.81 GiB 4.14% 5.256
DM Mathematics 7.75 GiB 3.64% 5.256
BookCorpus 6.30 GiB 2.96% 5.256
Ubuntu IRC 5.52 GiB 2.59% 5.256
CORD-19 4.26 GiB 2.00% 5.256
Enron Emails 901.43 MiB 0.41% 5.256
Total 212.63 GiB

Manual Download Components

The following components need manual downloading. Either download them or comment out from pile.py.

  • Bibliotik: books3.tar.gz needs to be in the current directory. Download temporarily unavailable.
  • CORD-19: document_parses needs to be in the current directory. Download from here.

Workflow

To propose a new dataset be added to the Pile, open an issue with the tag Proposed Dataset. Your issue should include a description of the dataset, its size, what language(s) it is in, a link to the data, and any other relevant information. If a project manger approves your proposal, they will change its label to Datasets and add it to Project: Datasets. Datasets that we elect to not include in the current version of the Pile will receive a Deferred or Declined label. While we welcome multilingual datasets and plan on including non-English datasets in the future, the initial release of the Pile will be English-only and all submissions of non-English datasets will be Deferred.

To claim an unclaimed dataset, leave a comment on one of our unassigned issues. Once an dataset has been assigned to you, make the necessary changes to datsets.py and pile.py in a fork and submit a pull request. If you require, you can also submit a script for processing the data as shown here.

To raise an issue that is not proposing a new dataset, open an issue with the tag Feature Request or Bug as appropriate.

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  • Python 100.0%