README.md

---
base_model: facebook/wav2vec2-base-960h
library_name: transformers.js
---

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](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@xenova/transformers) using:
```bash
npm i @xenova/transformers
```

You can then use the model for speech recognition with:

```js
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](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).