Add/update the quantized ONNX model files and README.md for Transformers.js v3 (#3)

- Add/update the quantized ONNX model files and README.md for Transformers.js v3 (7b8b5f2280cec38b4072f5683cfba289c97e4255)
- Upload README.md with huggingface_hub (300063ee0261c5ca694d7f1ad4db923dc4eca5bf)
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- Upload README.md with huggingface_hub (cd3fbe4b2bcc23ca61ae132bb42f28b00c60e8f6)
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Co-authored-by: Yuichiro Tachibana <whitphx@users.noreply.huggingface.co>

README.md

@@ -5,4 +5,20 @@ library_name: transformers.js
 
 https://huggingface.co/openai/whisper-large-v2 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:** Transcribe audio from a URL.
+
+```js
+import { pipeline } from '@huggingface/transformers';
+const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/whisper-large-v2');
+const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/jfk.wav';
+const output = await transcriber(url);
+```
+
 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`).

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onnx/decoder_with_past_model_bnb4.onnx

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