README.md

---
base_model: openai/whisper-tiny
library_name: transformers.js
---

https://huggingface.co/openai/whisper-tiny with ONNX weights to be compatible with 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/@huggingface/transformers) using:
```bash
npm i @huggingface/transformers
```

```js
import { pipeline } from '@huggingface/transformers';

// Create the pipeline
const transcriber = await pipeline('automatic-speech-recognition', 'whitphx/test-transformersjs-whisper-tiny', {
    dtype: 'fp32',  // Options: "fp32", "fp16", "q8", "q4"
});

// Use the model
const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/jfk.wav';
const output = await transcriber(url);
```

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`).