https://huggingface.co/superb/wav2vec2-base-superb-ks 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/wav2vec2-base-superb-ks
and return top 3 results.
import { pipeline } from '@huggingface/transformers';
// Create an audio classification pipeline
const classifier = await pipeline('audio-classification', 'Xenova/wav2vec2-base-superb-ks');
// Predict class
const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/speech-commands_down.wav';
const output = await classifier(url, { top_k: 3 });
console.log(output);
// [
// { label: 'down', score: 0.9998697638511658 },
// { label: 'go', score: 0.00009957332076737657 },
// { label: '_unknown_', score: 0.000029320701287360862 },
// ]
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.
Model tree for Xenova/wav2vec2-base-superb-ks
Base model
superb/wav2vec2-base-superb-ks