@sctg/sentencepiece-js
v1.3.3
Published
Sentencepiece tokenization for natural language processing, JS version.
Downloads
23
Maintainers
Readme
Javascript wrapper for the sentencepiece library
Browser Demo
You can see Sentencepiece-js in action for counting and displaying tokens using the Meta Llama 3.1 tokenizer model on GitHub Pages: https://sctg-development.github.io/sentencepiece-js/. All computations are performed in your browser, and no data is sent to the server. To display the tokens, click on the tokens
link.
This simple React app is located in the tokenCount
directory of this repository. It is built with React 18, Vite, and the Fluent UI v9 framework.
Build
Sentencepiece is compiled to webassembly using emscripten.
To rebuild this project
npm install
git clone --recurse-submodules https://github.com/sctg-development/sentencepiece-js.git
npm run build
Use
To use this tool in nodejs, you can use the following code:
const { SentencePieceProcessor, cleanText } = require("../dist");
const ROOT = require('app-root-path')
async function main() {
let text = "I am still waiting on my card?"
let cleaned = cleanText(text)
let spp = new SentencePieceProcessor()
await spp.load(`${ROOT}/test/30k-clean.model`)
let ids = spp.encodeIds(cleaned)
console.log(ids)
let str = spp.decodeIds(ids) // list ids->number
console.log(str)
let pieces = spp.encodePieces(cleaned) // list tokens->string
console.log(pieces)
}
main()
In the browser, you can use the following code (see the tokenCount
directory for a full example):
import { SentencePieceProcessor, cleanText, llama_3_1_tokeniser_b64 } from "@sctg/sentencepiece-js";
// built in models: llama_3_1_tokeniser_b64, clean_30k_b64, smart_b64
async function main() {
let text = "I am still waiting on my card?"
let cleaned = cleanText(text)
let spp = new SentencePieceProcessor()
await spp.loadFromB64StringModel(llama_3_1_tokeniser_b64);
let ids = spp.encodeIds(cleaned)
console.log(ids)
let str = spp.decodeIds(ids) // list ids->number
console.log(str)
let pieces = spp.encodePieces(cleaned) // list tokens->string
console.log(pieces)
}
main()
See https://github.com/sctg-development/ai-outlook/blob/HEAD/src/aipane/aipane.ts#L11-L23 for an example of how to use this in a react app.
Look also at webpack.config.js for the configuration of the webpack bundler.
- devilyouwei updated this repo to make this module support the js
require
keyword and added the using example. - 2023-1-10, devilyouwei added
encodePieces
. - original author: https://github.com/JanKaul/sentencepiece