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LREC-COLING 2024main

GPT-SW3: An Autoregressive Language Model for the Scandinavian Languages

Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

DOI:10.63317/2pg96oituizk

Abstract

This paper details the process of developing the first native large generative language model for the North Germanic languages, GPT-SW3. We cover all parts of the development process, from data collection and processing, training configuration and instruction finetuning, to evaluation, applications, and considerations for release strategies. We discuss pros and cons of developing large language models for smaller languages and in relatively peripheral regions of the globe, and we hope that this paper can serve as a guide and reference for other researchers that undertake the development of large generative models for smaller languages.

Details

Paper ID
lrec2024-main-0695
Pages
pp. 7886-7900
BibKey
ekgren-etal-2024-gpt
Editor
N/A
Publisher
European Language Resources Association (ELRA) and ICCL
ISSN
2522-2686
ISBN
979-10-95546-34-4
Conference
Joint International Conference on Computational Linguistics, Language Resources and Evaluation
Location
Turin, Italy
Date
20 May 2024 25 May 2024

Authors

  • AE

    Ariel Ekgren

  • AC

    Amaru Cuba Gyllensten

  • FS

    Felix Stollenwerk

  • Joey Öhman

  • TI

    Tim Isbister

  • EG

    Evangelia Gogoulou

  • FC

    Fredrik Carlsson

  • JC

    Judit Casademont

  • MS

    Magnus Sahlgren

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