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arXiv:2101.00027cs.CL

The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, Shawn Presser, Connor Leahy

Abstract

Recent work has demonstrated that increased training dataset diversity improves general cross-domain knowledge and downstream generalization capability for large-scale language models. With this in mind, we present \textit{the Pile}: an 825 GiB English text corpus targeted at training large-scale language models. The Pile is constructed from 22 diverse high-quality subsets -- both existing and newly constructed -- many of which derive from academic or professional sources. Our evaluation of the untuned performance of GPT-2 and GPT-3 on the Pile shows that these models struggle on many of its components, such as academic writing. Conversely, models trained on the Pile improve significantly over both Raw CC and CC-100 on all components of the Pile, while improving performance on downstream evaluations. Through an in-depth exploratory analysis, we document potentially concerning aspects of the data for prospective users. We make publicly available the code used in its construction.

arXiv comments
Journal reference
DOI
Subjects
cs.CLComputation and Language

On Hacker News

Linked by 22 identifiable commenters in 28 comments across 28 threads, from Mar 2021 to Apr 2026. Found in 3 HN submissions from May 2021 to Jul 2023. Open submission discussions.

Comments linking this paper, per year.

Discussed in comments28 threads

    • The article describes "the pile" as an "unfiltered scrape by design". But, the paper actually describes it as a bizarre mix of curated sources. https://arxiv.org/pdf/2101.00027 Generally, I find the LLMs are too overtrained on promotional materials and professional published…

      afpxView on HNParent context

    • I don't understand why it's even a question that Meta trained their LLM on copyrighted material. They say so in their paper! Quoting from their LLaMMa paper [Touvron et al., 2023]: > We include two book corpora in our training dataset: the Gutenberg Project, [...], and the…

      JW_00000View on HNParent context

    • I don’t see any source for that from their paper. It just says a duplicate version of Pile with a citation linking to the original Pile paper itself. [15] Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, An-ish Thite…

      yunohnView on HNParent context

  1. DBRX: A new open LLM 1 comment
    • Personally, I found looking at open source work to be much more instructive in learning about AI and how things like training data and such are done from the ground up. I suspect this is because training data is one of the bigger moats an AI company can have, as well as all the…

      IshanMiView on HNParent context

    • The Pile dataset for those interested https://pile.eleuther.ai/ https://arxiv.org/abs/2101.00027 I'm bullish on domain specific models that start from generalized models. Something of a T shape analogy, but maybe a couple of distillation & fine-tuning steps

      verdvermView on HNParent context

    • EleutherAI cleaned an OpenSubtitles dataset that was 12.98GiB (13.9GB). https://arxiv.org/abs/2101.00027 https://lifearchitect.ai/whats-in-my-ai/

      adtView on HNParent context

    • > What's the value of these The Pile (the 800GB dataset by Eluther AI) contains BookCorpus2, along with two much larger datasets of books (and a whole lot of not-book stuff). From their paper [0] the reasoning for the book datasets is that they are "are invaluable for long-range…

      wongarsuView on HNParent context

  2. What OpenAI really wants 1 comment
    • There are a bunch of datasets that people use for example "common crawl" and "The Pile" https://arxiv.org/abs/2101.00027 [1]. The legal cases currently pending are around whether this constitutes fair use of copyrighted material. [1] Which incorporates about 9GB of Hackernews…

      seanhunterView on HNParent context

    • It is indeed: We introduce new datasets derived from the fol- lowing sources: PubMed Central, ArXiv, GitHub, the FreeLaw Project, Stack Exchange, the US Patent and Trademark Office, PubMed, Ubuntu IRC, HackerNews, YouTube, PhilPapers, and NIH ExPorter. We also introduce…

      capablewebView on HNParent context

    • That's not how copyright law works at all. It doesn't say "well if you didn't want someone to copy this thing you should have stopped them from doing it". It lays out 4 factors for a court to consider about whether something is fair use and none of them are around how easy it…

      seanhunterView on HNParent context

    • Are we all reading the same complaint? They say: > in a Meta paper detailing LLaMA, the company points to sources for its training datasets, one of which is called ThePile, which was assembled by a company called EleutherAI. ThePile, the complaint points out, was described in an…

      edentView on HNParent context

    • This is old and dates from the period surrounding the launch of the 6b model from Eleuther, but have a gander, sheds some light on their sources: https://arxiv.org/abs/2101.00027 GPT4 technical paper doesn't seem to disclose it (or I didn't dive deep enough)…

      construct0View on HNParent context

    • The thought just occurred to me, does training data ordering have any impact on LLM loss? It's not a terrible experiment to try, right? There reason I'm asking is because we tend to educate humans using a fairly well-ordered path of curriculum. Take, for example, children's…

      kelseyfrogView on HNParent context

    • @article{pile, title={The {P}ile: An 800GB Dataset of Diverse Text for Language Modeling}, author={Gao, Leo and Biderman, Stella and Black, Sid and Golding, Laurence and Hoppe, Travis and Foster, Charles and Phang, Jason and He, Horace and Thite, Anish and Nabeshima, Noa and…

      hanselotView on HNParent context

    • The Pile already does! Part of its contents come from the "USPTO Backgrounds" dataset. From The Pile's paper: > USPTO Backgrounds is a dataset of background sections from patents granted by the United States Patent and Trademark Office, derived from its published bulk archives.…

      orpheansodalityView on HNParent context

    • From The Pile: An 800GB Dataset of Diverse Text for Language Modeling: https://arxiv.org/pdf/2101.00027.pdf 7.1 Legality of Content While the machine learning community has begun to discuss the issue of the legality of training models on copyright data, there is little…

      williamcottonView on HNParent context

    • You're right, I wasn't clear. But I'm a full-time ML researcher. In terms of advancing the field, my contributions so far have been modest, but they're there. Some of my favorite ideas were swarm training (https://battle.shawwn.com/swarm-training-v01a.pdf), stop loss for…

      sillysaurusxView on HNParent context

    • Sure, if you think it’d help. Here’s the message I sent that got me the new job. The context is that they were pushing back a little bit during salary negotiation and asking for a resume, so I channeled my Jewish ancestors and went into full salesman mode: “…

      sillysaurusxView on HNParent context

    • > "power" [comes from] the entire Internet Are you sure? See "the Pile": https://pile.eleuther.ai/ The paper cited there by contrast, argues for select training sets: Recent work has demonstrated that increased training dataset diversity improves general cross-domain knowledge…

      TerrettaView on HNParent context

    • You're using it right. The poster above doesn't like Magic 8 Ball. So how about "abacus"? An accountant with an abacus is better at accounting than one without, but the abacus has no idea what accounting or math are, it can't even count. This thing is a remarkable abacus for…

      TerrettaView on HNParent context

    • Yes. EleutherAI is doing it, probably one of many: https://www.eleuther.ai/projects/gpt-neox/ https://github.com/EleutherAI/gpt-neox https://arxiv.org/abs/2204.06745 They have a 20B parameter model. I think the primary dataset for these open models is The Pile…

      cottonseedView on HNParent context

    • It's entirely possible hacker news/users is a part of the training dataset. It was a part of The Pile (https://arxiv.org/abs/2101.00027), and we included usernames along with the item. Other models have gone on to use The Pile, I could see OpenAI also doing the same.

      aquajetView on HNParent context

    • It's mentioned somewhere in here (https://arxiv.org/abs/2101.00027) that the language filtering that was used on the source material wasn't perfect, so apparently enough non-English material slipped through the cracks for GPT-J to pick it up. I tried it extensively with German –…

      iggldigglView on HNParent context

    • Unfortunately, it's 2:45am, and I have a meeting tomorrow. But I'll try to set aside some time for a detailed reply. The cliff's notes are: the first time I was able to train GPT 1.5B on gwern's poetry, I was super proud of myself, because it was extremely hard to get 1.5B to…

      sillysaurusxView on HNParent context

    • They super earned it. From day one, everyone showed up with a level of drive and determination I haven't seen elsewhere. My name is on The Pile paper https://arxiv.org/abs/2101.00027 but I didn't do anything except make the books3 dataset. Stella, Leo, and everyone else did the…

      sillysaurusxView on HNParent context

    • > the Eleuther team has curated and released a high-quality text data set known as the Pile for training NLP algorithms. This includes HN [i] HackerNews 3.90GiB 0.62% Which if SciFi has taught me anything means we are all uploaded now and will live forever. [i]…

      aaron695View on HNParent context

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