Update README.md

README.md

@@ -4,4 +4,39 @@ library_name: transformers.js
 
 https://huggingface.co/OFA-Sys/chinese-clip-vit-base-patch16 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:** Zero-shot image classification w/ `Xenova/chinese-clip-vit-base-patch16`.
+
+```javascript
+import { pipeline } from '@xenova/transformers';
+
+// Create zero-shot image classification pipeline
+const classifier = await pipeline('zero-shot-image-classification', 'Xenova/chinese-clip-vit-base-patch16');
+
+// Set image url and candidate labels
+const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/pikachu.png';
+const candidate_labels = ['杰尼龟', '妙蛙种子', '小火龙', '皮卡丘'] // Squirtle, Bulbasaur, Charmander, Pikachu in Chinese
+
+// Classify image
+const output = await classifier(url, candidate_labels);
+console.log(output);
+// [
+//   { score: 0.9926728010177612, label: '皮卡丘' },        // Pikachu
+//   { score: 0.003480620216578245, label: '妙蛙种子' },    // Bulbasaur
+//   { score: 0.001942147733643651, label: '杰尼龟' },      // Squirtle
+//   { score: 0.0019044597866013646, label: '小火龙' }      // Charmander
+// ]
+```
+
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/bVOErVl5Zsz1dpstDfKpu.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`).