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 JavaScript library from NPM using:
npm i @huggingface/transformers
Example: Perform audio classification with Xenova/ast-finetuned-audioset-10-10-0.4593 and return top 4 results.
import { pipeline } from '@huggingface/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, { top_k: 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 and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).