Tokenizers documentation

Tokenizers

Hugging Face's logo
Join the Hugging Face community

and get access to the augmented documentation experience

to get started

Tokenizers

Fast State-of-the-art tokenizers, optimized for both research and production

🤗 Tokenizers provides an implementation of today’s most used tokenizers, with a focus on performance and versatility. These tokenizers are also used in 🤗 Transformers.

Main features:

  • Train new vocabularies and tokenize, using today’s most used tokenizers.
  • Extremely fast (both training and tokenization), thanks to the Rust implementation. Takes less than 20 seconds to tokenize a GB of text on a server’s CPU.
  • Easy to use, but also extremely versatile.
  • Designed for both research and production.
  • Full alignment tracking. Even with destructive normalization, it’s always possible to get the part of the original sentence that corresponds to any token.
  • Does all the pre-processing: Truncation, Padding, add the special tokens your model needs.