In the world of AI, Large Language Models (LLMs) are at the forefront, revolutionizing how we interact with technology. However, despite their impressive capabilities, LLMs have limitations that must be addressed.
Two prominent methods for enhancing the performance of LLMs are Retrieval Augmented Generation (RAG) and Fine Tuning.
This article explores these methods, their benefits, and their drawbacks, helping you decide which one best suits your needs.
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