For text, an algorithm segments characters or bytes into vocabulary entries and maps them to integer identifiers. The same tokenizer must decode outputs and remain compatible with the model's learned embedding table.
Tokenization converts raw input into discrete units that a model can represent and process.
For text, an algorithm segments characters or bytes into vocabulary entries and maps them to integer identifiers. The same tokenizer must decode outputs and remain compatible with the model's learned embedding table.