Update README.md

README.md

@@ -5,4 +5,34 @@ base_model: facebook/dinov2-with-registers-large-imagenet1k-1-layer
 
 https://huggingface.co/facebook/dinov2-with-registers-large-imagenet1k-1-layer 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/@huggingface/transformers) using:
+```bash
+npm i @huggingface/transformers
+```
+
+**Example:** Image classification w/ `onnx-community/dinov2-with-registers-large-imagenet1k-1-layer`.
+
+```javascript
+import { pipeline } from '@huggingface/transformers';
+
+// Create image classification pipeline
+const classifier = await pipeline('image-classification', 'onnx-community/dinov2-with-registers-large-imagenet1k-1-layer');
+
+// Classify an image
+const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg';
+const output = await classifier(url);
+console.log(output);
+// [
+//   { label: 'tabby, tabby cat', score: 0.5210835337638855 },
+//   { label: 'Egyptian cat', score: 0.313551127910614 },
+//   { label: 'tiger cat', score: 0.14324277639389038 },
+//   { label: 'lynx, catamount', score: 0.005053747445344925 },
+//   { label: 'remote control, remote', score: 0.001643550000153482 }
+// ]
+```
+
+---
+
 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`).