Kavsar Huseynova
2024
Open foundation models for Azerbaijani language
Jafar Isbarov
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Kavsar Huseynova
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Elvin Mammadov
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Mammad Hajili
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Duygu Ataman
Proceedings of the First Workshop on Natural Language Processing for Turkic Languages (SIGTURK 2024)
The emergence of multilingual large language models has enabled the development of language understanding and generation systems in Azerbaijani. However, most of the production-grade systems rely on cloud solutions, such as GPT-4. While there have been several attempts to develop open foundation models for Azerbaijani, these works have not found their way into common use due to a lack of systemic benchmarking. This paper encompasses several lines of work that promote open-source foundation models for Azerbaijani. We introduce (1) a large text corpus for Azerbaijani, (2) a family of encoder-only language models trained on this dataset, (3) labeled datasets for evaluating these models, and (4) extensive evaluation that covers all major open-source models with Azerbaijani support.
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