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 (8ef7d3a0972bbb55e1e4c56023fc237cace30188)


Co-authored-by: Yuichiro Tachibana <whitphx@users.noreply.huggingface.co>

README.md

@@ -6,4 +6,22 @@ pipeline_tag: zero-shot-object-detection
 
 https://huggingface.co/google/owlvit-base-patch16 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:** Zero-shot object detection.
+
+```js
+import { pipeline } from '@huggingface/transformers';
+
+const detector = await pipeline('zero-shot-object-detection', 'Xenova/owlvit-base-patch16');
+const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/astronaut.png';
+const candidate_labels = ['human face', 'rocket', 'helmet', 'american flag'];
+const output = await detector(url, candidate_labels);
+```
+
 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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+size 182206705

onnx/model_q4.onnx

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onnx/model_q4f16.onnx

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onnx/model_uint8.onnx

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