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---
base_model: facebook/convnext-large-384-22k-1k
library_name: transformers.js
---
https://huggingface.co./facebook/convnext-large-384-22k-1k 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 image classification with `Xenova/convnext-large-384-22k-1k`.
```js
import { pipeline } from '@xenova/transformers';
// Create image classification pipeline
const classifier = await pipeline('image-classification', 'Xenova/convnext-large-384-22k-1k');
// 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)
```
---
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`). |