Update README.md

README.md

@@ -4,4 +4,48 @@ library_name: transformers.js
 
 https://huggingface.co/jonathandinu/face-parsing 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:** Face segmentation with `Xenova/face-parsing`.
+
+```js
+import { pipeline } from '@xenova/transformers';
+
+const segmenter = await pipeline('image-segmentation', 'Xenova/face-parsing');
+
+const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/portrait-of-woman.jpg';
+const output = await segmenter(url);
+console.log(output)
+// [
+//   {
+//     score: null,
+//     label: 'background',
+//     mask: RawImage { ... }
+//   },
+//   {
+//     score: null,
+//     label: 'skin.png',
+//     mask: RawImage { ... }
+//   },
+//   ...
+//   }
+// ]
+```
+
+You can visualize the outputs with:
+```js
+for (const l of output) {
+  l.mask.save(`${l.label}.png`);
+}
+```
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/530NS10pjaIlycdGWp9E9.png)
+
+---
+
 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`).