Update README.md

README.md

@@ -5,4 +5,30 @@ library_name: transformers.js
 
 https://huggingface.co/Salesforce/codegen-350M-mono 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:** Code completion w/ `Xenova/codegen-350M-mono`.
+```js
+import { pipeline } from "@huggingface/transformers";
+
+// Create a text generation pipeline
+const generator = await pipeline("text-generation", "Xenova/codegen-350M-mono");
+
+// Define the prompt
+const text = `def fib(n):
+    """Calculates the nth Fibonacci number"""`;
+
+// Generate a response
+const output = await generator(text, { max_new_tokens: 45 });
+console.log(output[0].generated_text);
+```
+
+---
+
 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`).