OLMo: Accelerating the Science of Language Models Dirk Groenevelda Iz Beltagya

Pete Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Harsh Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Raghavi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob MorrisonNiklas Muennighoff Aakanksha Naik, Crystal Nam, Matthew E. Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, Will Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah A. Smith, Hannaneh Hajishirzi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Language models (LMs) have become ubiquitous in both NLP research and in commercial product offerings. As their commercial importance has surged, the most powerful models have become closed off, gated behind proprietary interfaces, with important details of their training data, architectures, and development undisclosed. Given the importance of these details in scientifically studying these models, including their biases and potential risks, we believe it is essential for the research community to have access to powerful, truly open LMs. To this end, we have built OLMo, a competitive, truly Open Language Model, to enable the scientific study of language models. Unlike most prior efforts that have only released model weights and inference code, we release OLMo alongside open training data and training and evaluation code. We hope this release will empower the open research community and inspire a new wave of innovation.

Original languageEnglish
Title of host publicationLong Papers
EditorsLun-Wei Ku, Andre F. T. Martins, Vivek Srikumar
PublisherAssociation for Computational Linguistics (ACL)
Pages15789-15809
Number of pages21
ISBN (Electronic)9798891760943
DOIs
StatePublished - 2024
Externally publishedYes
Event62nd Annual Meeting of the Association for Computational Linguistics, ACL 2024 - Bangkok, Thailand
Duration: 11 Aug 202416 Aug 2024

Publication series

NameProceedings of the Annual Meeting of the Association for Computational Linguistics
Volume1
ISSN (Print)0736-587X

Conference

Conference62nd Annual Meeting of the Association for Computational Linguistics, ACL 2024
Country/TerritoryThailand
CityBangkok
Period11/08/2416/08/24

Bibliographical note

Publisher Copyright:
© 2024 Association for Computational Linguistics.

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