# Tokenizers

Not supported by the rc0 bindings yet. rc0 loads a `tokenizer.json` and encodes and
decodes with it — building a tokenizer from its components, editing one, saving one
and training are not exposed. They are coming soon, along with the other bindings.
See [`REQUIRED_FOR_V1.md`](https://github.com/huggingface/tokenizers/blob/main/REQUIRED_FOR_V1.md) for the full list.

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

[🤗 Tokenizers](https://github.com/huggingface/tokenizers) provides an
implementation of today's most used tokenizers, with a focus on
performance and versatility. These tokenizers are also used in [🤗 Transformers](https://github.com/huggingface/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.