@anush008/tokenizers v0.0.0

@anush008/tokenizers

Multi-arch bindings for @huggingface/tokenizers.

Supports:

• Windows x86_64
• Linux x86_64
• MacOS aarch64/x86_64

Installation

npm install @anush008/tokenizers

Features

• 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.

Basic example

import { Tokenizer } from "@anush008/tokenizers";

const tokenizer = await Tokenizer.fromFile("tokenizer.json");
const wpEncoded = await tokenizer.encode("Who is John?");

console.log(wpEncoded.getLength());
console.log(wpEncoded.getTokens());
console.log(wpEncoded.getIds());
console.log(wpEncoded.getAttentionMask());
console.log(wpEncoded.getOffsets());
console.log(wpEncoded.getOverflowing());
console.log(wpEncoded.getSpecialTokensMask());
console.log(wpEncoded.getTypeIds());
console.log(wpEncoded.getWordIds());

License

MIT