From Bytes to Borsch: Fine-Tuning Gemma and Mistral for the Ukrainian Language Representation

arXiv:2404.09138v1 Announce Type: cross
Abstract: 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 and generation. However, the limited representation of low-resource languages like Ukrainian poses a notable challenge, restricting the reach and relevance of this technology. Our paper addresses this by fine-tuning the open-source Gemma and Mistral LLMs with Ukrainian datasets, aiming to improve their linguistic proficiency and benchmarking them against other …

abstract arxiv challenge cs.ai cs.cl cs.lg fine-tuning gemma generative however innovation language language models languages large language large language models llms low mistral nlp representation text text understanding type understanding