OLMo: Accelerating the Science of Language Models
Dirk Groeneveld, Iz Beltagy, Evan Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, William Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah Smith, Hannaneh Hajishirzi
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.- Anthology ID:
- 2024.acl-long.841
- Volume:
- Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Lun-Wei Ku, Andre Martins, Vivek Srikumar
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 15789–15809
- Language:
- URL:
- https://aclanthology.org/2024.acl-long.841
- DOI:
- 10.18653/v1/2024.acl-long.841
- Bibkey:
- Cite (ACL):
- Dirk Groeneveld, Iz Beltagy, Evan Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, et al.. 2024. OLMo: Accelerating the Science of Language Models. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 15789–15809, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- OLMo: Accelerating the Science of Language Models (Groeneveld et al., ACL 2024)
- Copy Citation:
- PDF:
- https://aclanthology.org/2024.acl-long.841.pdf
Export citation
@inproceedings{groeneveld-etal-2024-olmo,
title = "{OLM}o: Accelerating the Science of Language Models",
author = "Groeneveld, Dirk and
Beltagy, Iz and
Walsh, Evan and
Bhagia, Akshita and
Kinney, Rodney and
Tafjord, Oyvind and
Jha, Ananya and
Ivison, Hamish and
Magnusson, Ian and
Wang, Yizhong and
Arora, Shane and
Atkinson, David and
Authur, Russell and
Chandu, Khyathi and
Cohan, Arman and
Dumas, Jennifer and
Elazar, Yanai and
Gu, Yuling and
Hessel, Jack and
Khot, Tushar and
Merrill, William and
Morrison, Jacob and
Muennighoff, Niklas and
Naik, Aakanksha and
Nam, Crystal and
Peters, Matthew and
Pyatkin, Valentina and
Ravichander, Abhilasha and
Schwenk, Dustin and
Shah, Saurabh and
Smith, William and
Strubell, Emma and
Subramani, Nishant and
Wortsman, Mitchell and
Dasigi, Pradeep and
Lambert, Nathan and
Richardson, Kyle and
Zettlemoyer, Luke and
Dodge, Jesse and
Lo, Kyle and
Soldaini, Luca and
Smith, Noah and
Hajishirzi, Hannaneh",
editor = "Ku, Lun-Wei and
Martins, Andre and
Srikumar, Vivek",
booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.acl-long.841",
doi = "10.18653/v1/2024.acl-long.841",
pages = "15789--15809",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings %T OLMo: Accelerating the Science of Language Models %A Groeneveld, Dirk %A Beltagy, Iz %A Walsh, Evan %A Bhagia, Akshita %A Kinney, Rodney %A Tafjord, Oyvind %A Jha, Ananya %A Ivison, Hamish %A Magnusson, Ian %A Wang, Yizhong %A Arora, Shane %A Atkinson, David %A Authur, Russell %A Chandu, Khyathi %A Cohan, Arman %A Dumas, Jennifer %A Elazar, Yanai %A Gu, Yuling %A Hessel, Jack %A Khot, Tushar %A Merrill, William %A Morrison, Jacob %A Muennighoff, Niklas %A Naik, Aakanksha %A Nam, Crystal %A Peters, Matthew %A Pyatkin, Valentina %A Ravichander, Abhilasha %A Schwenk, Dustin %A Shah, Saurabh %A Smith, William %A Strubell, Emma %A Subramani, Nishant %A Wortsman, Mitchell %A Dasigi, Pradeep %A Lambert, Nathan %A Richardson, Kyle %A Zettlemoyer, Luke %A Dodge, Jesse %A Lo, Kyle %A Soldaini, Luca %A Smith, Noah %A Hajishirzi, Hannaneh %Y Ku, Lun-Wei %Y Martins, Andre %Y Srikumar, Vivek %S Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) %D 2024 %8 August %I Association for Computational Linguistics %C Bangkok, Thailand %F groeneveld-etal-2024-olmo %X 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. %R 10.18653/v1/2024.acl-long.841 %U https://aclanthology.org/2024.acl-long.841 %U https://doi.org/10.18653/v1/2024.acl-long.841 %P 15789-15809
Markdown (Informal)
[OLMo: Accelerating the Science of Language Models](https://aclanthology.org/2024.acl-long.841) (Groeneveld et al., ACL 2024)
- OLMo: Accelerating the Science of Language Models (Groeneveld et al., ACL 2024)
ACL
- Dirk Groeneveld, Iz Beltagy, Evan Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, et al.. 2024. OLMo: Accelerating the Science of Language Models. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 15789–15809, Bangkok, Thailand. Association for Computational Linguistics.