What is an Out-Of-Vocabulary (OOV) token?
A word or character the tokenizer doesn't recognize, which is replaced by a special [UNK] token.
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More FAQs in What is Tokenization and How do LLMs Read Text?
Subwords allow the model to handle typos, prefixes, and suffixes efficiently without expanding the vocabulary index into millions of words.
LLM providers charge per token processed, not per word or character. Long prompts cost more because they translate to more tokens.
Emojis are represented by multiple unicode bytes, which often get split into multiple tokens by the tokenizer.
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