How Tokenization Works in LLMs: Exploring Byte Pair Encoding

In this video, we explore the fascinating process of tokenization in Large Language Models (LLMs), with a focus on Byte Pair Encoding (BPE). Tokenization is a crucial step in transforming raw text into a format that LLMs can understand, and BPE is one of the most effective methods used. We'll break down how Byte Pair Encoding works, why it's important for improving model efficiency, and how it handles subword units to balance vocabulary size and accuracy. Whether you're new to machine learning or looking to deepen your understanding of LLMs, this video will provide you with clear insights into one of the core techniques in NLP (Natural Language Processing). Don't forget to like, subscribe, and hit the notification bell for more in-depth discussions on machine learning and NLP! Reference: - https://neptune.ai/blog/tokenization-in-nlp - https://towardsdatascience.com/byte-pair-encoding-subword-based-tokenization-algorithm-77828a70bee0 #Tokenization #BytePairEncoding #LLMs #MachineLearning #NLP #AI #NaturalLanguageProcessing