Provides an implementation of today's most used tokenizers, with a focus on performance and versatility.

Main features:

• Train new vocabularies and tokenize, using todays 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 research and production.
• Normalization comes with alignments tracking. It's always possible to get the part of the original sentence that corresponds to a given token.
• Does all the pre-processing: Truncate, Pad, add the special tokens your model needs.

Bindings

We provide bindings to the following languages (more to come!):

• Python
• Node.js