|
--- |
|
library_name: transformers.js |
|
--- |
|
|
|
https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593 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 |
|
``` |
|
|
|
**Example:** Perform audio classification with `Xenova/ast-finetuned-audioset-10-10-0.4593` and return top 4 results. |
|
```js |
|
import { pipeline } from '@xenova/transformers'; |
|
|
|
// Create an audio classification pipeline |
|
const classifier = await pipeline('audio-classification', 'Xenova/ast-finetuned-audioset-10-10-0.4593'); |
|
|
|
// Predict class |
|
const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cat_meow.wav'; |
|
const output = await classifier(url, { topk: 4 }); |
|
console.log(output); |
|
// [ |
|
// { label: 'Meow', score: 0.5617874264717102 }, |
|
// { label: 'Cat', score: 0.22365376353263855 }, |
|
// { label: 'Domestic animals, pets', score: 0.1141069084405899 }, |
|
// { label: 'Animal', score: 0.08985692262649536 }, |
|
// ] |
|
``` |
|
|
|
--- |
|
|
|
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`). |