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/microsoft/beit-base-patch16-384 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:** Classify an image.
+
+```js
+import { pipeline } from '@huggingface/transformers';
+
+const classifier = await pipeline('image-classification', 'Xenova/beit-base-patch16-384');
+const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/tiger.jpg';
+const output = await classifier(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

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ecce4d94925be5fa2f6d1c1b0a66a8dba94b77af814fd472726df7f7beb29ae1
+size 245722187

onnx/model_q4.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4d24b53c1cac8fe3d3cc2ae22ccd8f077c8be722caeb46846bd5c3c65d0dfd24
+size 251030075

onnx/model_q4f16.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7d20368578cd64363af9f928557a22399e818c495be0272573bcd55e16db3da9
+size 146856438

onnx/model_uint8.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2d1dc47d24b45b08a7a8c7fae90e0d39b2cc28fba4dd95dab019542c0f402786
+size 278892608