Update README.md

README.md

@@ -4,4 +4,33 @@ library_name: transformers.js
 
 https://huggingface.co/facebook/hiera-base-224-in1k-hf 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:** Perform image classification with `onnx-community/hiera-base-224-in1k-hf`
+```js
+import { pipeline } from '@huggingface/transformers';
+
+// Create an image classification pipeline
+const classifier = await pipeline('image-classification', 'onnx-community/hiera-base-224-in1k-hf');
+
+// 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: 0.759323239326477 },
+// { label: 'tiger cat', score: 0.08907650411128998 },
+// { label: 'lynx, catamount', score: 0.0008640264859423041 },
+// { label: 'jaguar, panther, Panthera onca, Felis onca', score: 0.0007982379174791276 },
+// { label: 'leopard, Panthera pardus', score: 0.00041627752943895757 }
+// ]
+```
+
+---
+
 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`).