Xenova/convnext-tiny-224

https://huggingface.co./facebook/convnext-tiny-224 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 @xenova/transformers

Example: Perform image classification with Xenova/convnext-tiny-224.

import { pipeline } from '@xenova/transformers';

// Create image classification pipeline
const classifier = await pipeline('image-classification', 'Xenova/convnext-tiny-224');

// Classify an image
const url = 'https://huggingface.co./datasets/Xenova/transformers.js-docs/resolve/main/tiger.jpg';
const output = await classifier(url);
console.log(output)
// [{ label: 'tiger, Panthera tigris', score: 0.6153212785720825 }]

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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).