metadata
base_model: facebook/hubert-large-ls960-ft
library_name: transformers.js
https://huggingface.co/facebook/hubert-large-ls960-ft with ONNX weights to be compatible with Transformers.js.
Usage (Transformers.js)
If you haven't already, you can install the Transformers.js JavaScript library from NPM using:
npm i @xenova/transformers
Example: Perform automatic speech recognition with Xenova/hubert-large-ls960-ft.
import { pipeline } from '@xenova/transformers';
// Create automatic speech recognition pipeline
const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/hubert-large-ls960-ft');
// Transcribe audio
const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/jfk.wav';
const output = await transcriber(url);
// { text: 'AND SO MY FELLOW AMERICA ASK NOT WHAT YOUR COUNTRY CAN DO FOR YOU ASK WHAT YOU CAN DO FOR YOUR COUNTRY' }
Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).