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Résumé : In recent years, large language models (LLMs) have revolutionized the field of machine learning (ML), demonstrating unprecedented capabilities in natural language processing (NLP) tasks. This review provides an in-depth analysis of the evolution, architectural innovations, training techniques, applications, evaluation metrics, and challenges associated with LLMs. By exploring both the advancements and the limitations of current LLMs, this paper aims to offer insights into the future directions for research and development in this dynamic field.