https://huggingface.co/facebook/wav2vec2-base-960h 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
You can then use the model for speech recognition with:
import { pipeline } from '@xenova/transformers';
// Create an Automatic Speech Recognition pipeline
const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/wav2vec2-base-960h');
// 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 AMERICAN AND NOT WHAT YOUR COUNTRY CAN DO FOR YOU AND 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
).
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Inference API (serverless) does not yet support transformers.js models for this pipeline type.
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facebook/wav2vec2-base-960h