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cs.CL2024
From English-Centric to Effective Bilingual: LLMs with Custom Tokenizers for Underrepresented Languages
Artur Kiulian, Anton Polishko, Mykola Khandoga +10
In this paper, we propose a model-agnostic cost-effective approach to developing bilingual base large language models (LLMs) to support English and any target language. The method…
cs.CL2024
From Bytes to Borsch: Fine-Tuning Gemma and Mistral for the Ukrainian Language Representation
Artur Kiulian, Anton Polishko, Mykola Khandoga +4
In the rapidly advancing field of AI and NLP, generative large language models (LLMs) stand at the forefront of innovation, showcasing unparalleled abilities in text understanding…