The size of a token in AI models can vary depending on the specific model, algorithm, and application. However, I can provide some general insights and examples:
- Word-level tokens: In many NLP models, a token is equivalent to a single word. For example, in a language model, a token might be a single word like "hello", "AI", or "machine".
- Subword-level tokens: Some models use subword-level tokens, which are smaller units of words. For example, in a wordpiece tokenization algorithm, a token might be a subword like "hel-" from the word "hello" or "arti-" from the word "artificial".