GPT-SW3: An Autoregressive Language Model for the Nordic Languages
Ariel Ekgren
Amaru Cuba Gyllensten
Felix Stollenwerk
Joey Öhman
T. Isbister
Evangelia Gogoulou
F. Carlsson
Alice Heiman
Judit Casademont
Magnus Sahlgren

Abstract
This paper details the process of developing the first native large generative language model for the Nordic languages, GPT-SW3. We cover all parts of the development process, from data collection and processing, training configuration and instruction finetuning, to evaluation and considerations for release strategies. 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.
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