Update README.md

README.md

@@ -1,7 +1,54 @@
 ---
 library_name: transformers.js
+base_model:
+- ibm-granite/granite-3.0-2b-instruct
 ---
 
 https://huggingface.co/ibm-granite/granite-3.0-2b-instruct 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:** Text generation with `onnx-community/granite-3.0-2b-instruct`.
+
+```js
+import { pipeline } from "@huggingface/transformers";
+
+// Create a text generation pipeline
+const generator = await pipeline(
+  "text-generation",
+  "onnx-community/granite-3.0-2b-instruct",
+  { dtype: "q4" },
+);
+
+// Define the list of messages
+const messages = [
+  { role: "system", content: "You are a helpful assistant." },
+  { role: "user", content: "Tell me a joke." },
+];
+
+// Generate a response
+const output = await generator(messages, { max_new_tokens: 128 });
+console.log(output[0].generated_text.at(-1).content);
+```
+
+<details>
+
+<summary>Example output</summary>
+
+```
+Why don't scientists trust atoms?
+
+Because they make up everything!
+```
+</details>
+
+
+---
+
 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`).