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

README.md

@@ -5,4 +5,21 @@ library_name: transformers.js
 
 https://huggingface.co/hf-tiny-model-private/tiny-random-Swin2SRModel 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:** Perform image feature extraction.
+
+```js
+import { pipeline } from '@huggingface/transformers';
+
+const image_feature_extractor = await pipeline('image-feature-extraction', 'Xenova/tiny-random-Swin2SRModel');
+const url = 'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/cats.png';
+const features = await image_feature_extractor(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`).

onnx/model_bnb4.onnx

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onnx/model_q4.onnx

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onnx/model_q4f16.onnx

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onnx/model_uint8.onnx

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