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GPT-SW3: a foundational model for Swedish NLP

Reference number
Coordinator Lindholmen Science Park AB - AI Sweden
Funding from Vinnova SEK 6 147 484
Project duration September 2022 - September 2024
Status Ongoing
Venture AI - Leading and innovation
Call Advanced and innovative AI

Important results from the project

The purpose of the project was to evaluate GPT-SW3, a family of large-scale Swedish language models, to assess its applicability in various tasks within the public sector and industry. The goal of testing and validating the models in practical use cases has been achieved through collaborations with multiple partners who have tested the model in areas such as summarization, categorization, and text generation. The results have provided valuable insights into the potential and limitations.

Expected long term effects

The project has resulted in a deeper understanding of how GPT-SW3 and the underlying technology can be applied in practice. Several partners have identified potential use cases but also challenges such as limited performance compared to other models, legal obstacles, and technical constraints. The project has thus contributed to knowledge building around large-scale language models in Sweden and created conditions for future development and implementation of AI technology across various sectors.

Approach and implementation

The project was executed through collaborations with the project partners, who tested GPT-SW3 within their respective organizations. This setup allowed for a broad evaluation of the model in various contexts. However, some partners highlighted the need for better coordination and continuous communication to maximize knowledge exchange and efficiency. The project successfully identified key insights and established a network for future collaboration on AI and language models in Sweden.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 31 October 2024

Reference number 2022-00949