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 (2469d95dda67317b980a0daaccba03e97e3daec3)


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

README.md

@@ -7,3 +7,21 @@ base_model:
 # llama-ai4privacy-multilingual-categorical-anonymiser-openpii (ONNX)
 
 This is an ONNX version of [ai4privacy/llama-ai4privacy-multilingual-categorical-anonymiser-openpii](https://huggingface.co/ai4privacy/llama-ai4privacy-multilingual-categorical-anonymiser-openpii). It was automatically converted and uploaded using [this space](https://huggingface.co/spaces/onnx-community/convert-to-onnx).
+
+## 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 named entity recognition.
+
+```js
+import { pipeline } from '@huggingface/transformers';
+
+const classifier = await pipeline('token-classification', 'onnx-community/llama-ai4privacy-multilingual-categorical-anonymiser-openpii-ONNX');
+const output = await classifier('My name is Sarah and I live in London');
+```
+
+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`).