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 (fab044ddd615402a86eae6ac7e35bb5f289f38f4)


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

README.md

@@ -5,4 +5,20 @@ library_name: transformers.js
 
 https://huggingface.co/avsolatorio/GIST-small-Embedding-v0 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:** Run feature extraction.
+
+```js
+import { pipeline } from '@huggingface/transformers';
+
+const extractor = await pipeline('feature-extraction', 'Xenova/GIST-small-Embedding-v0');
+const output = await extractor('This is a simple test.');
+```
+
 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_q4f16.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b37db10fc998fe3ca7360174efea0f65fcd3a7860577677e17ab9d4ead390ebd
+size 36190172