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Answer Posted / Saurabh Gautam
Tokenization is essential in Langauge Models (LLMs) as it converts raw text into sequences of tokens. Each token represents a meaningful unit, such as words or subwords, which the model processes individually. Tokenization makes it possible for models to handle variable-length inputs and facilitates efficient training by reducing dimensionality.
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