https://huggingface.co/facebook/dinov2-small 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 image feature extraction.

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

const image_feature_extractor = await pipeline('image-feature-extraction', 'Xenova/dinov2-small');
const url = 'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/cats.png';
const features = await image_feature_extractor(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 ๐Ÿค— Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).

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