NodeJS implementation of today's most used tokenizers, with a focus on performance and versatility. Bindings over the Rust implementation. If you are interested in the High-level design, you can go check it there.
- Train new vocabularies and tokenize using 4 pre-made tokenizers (Bert WordPiece and the 3 most common BPE versions).
- 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.
npm install tokenizers@latest
BPETokenizer: The original BPE
ByteLevelBPETokenizer: The byte level version of the BPE
SentencePieceBPETokenizer: A BPE implementation compatible with the one used by SentencePiece
BertWordPieceTokenizer: The famous Bert tokenizer, using WordPiece