Update README.md

README.md

@@ -4,4 +4,36 @@ library_name: transformers.js
 
 https://huggingface.co/facebook/hubert-base-ls960 with ONNX weights to be compatible with Transformers.js.
 
+https://huggingface.co/laion/larger_clap_music_and_speech 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:** Load and run a `HubertModel` for feature extraction.
+```javascript
+import { AutoProcessor, AutoModel, read_audio } from '@xenova/transformers';
+
+// Read and preprocess audio
+const processor = await AutoProcessor.from_pretrained('Xenova/hubert-base-ls960');
+const audio = await read_audio('https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/jfk.wav', 16000);
+const inputs = await processor(audio);
+
+// Load and run model with inputs
+const model = await AutoModel.from_pretrained('Xenova/hubert-base-ls960');
+const output = await model(inputs);
+// {
+//   last_hidden_state: Tensor {
+//     dims: [ 1, 549, 768 ],
+//     type: 'float32',
+//     data: Float32Array(421632) [0.0682469978928566, 0.08104046434164047, -0.4975186586380005, ...],
+//     size: 421632
+//   }
+// }
+```
+---
+
 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`).