Add/update the quantized ONNX model files and README.md for Transformers.js v3 (#1)

- Add/update the quantized ONNX model files and README.md for Transformers.js v3 (90bf91a0bca1faf76526430853786147988807d9)
- Upload README.md with huggingface_hub (6015e7bc5ad86618b3c6a3f7145f1809e59f33b0)
- Upload README.md with huggingface_hub (afaad51f832a09e5996be898ddeedbdc4f87870b)
- Upload README.md with huggingface_hub (d72a52c019d8f91c7d4c397b4ff28f0b832d3fe4)


Co-authored-by: Yuichiro Tachibana <[email protected]>

README.md

@@ -5,4 +5,17 @@ library_name: transformers.js
 
 https://huggingface.co/bh4/whisper-ben with ONNX weights to be compatible with 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
+```
+
+```js
+import { pipeline } from '@huggingface/transformers';
+
+const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/whisper-ben');
+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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