Add/update the quantized ONNX model files and README.md for Transformers.js v3
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README.md
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# llama-ai4privacy-multilingual-categorical-anonymiser-openpii (ONNX)
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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).
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# llama-ai4privacy-multilingual-categorical-anonymiser-openpii (ONNX)
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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).
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## Usage (Transformers.js)
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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:
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```bash
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npm i @huggingface/transformers
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```
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**Example:** Perform named entity recognition.
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```js
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import { pipeline } from '@huggingface/transformers';
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const classifier = await pipeline('token-classification', 'onnx-community/llama-ai4privacy-multilingual-categorical-anonymiser-openpii-ONNX');
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const output = await classifier('My name is Sarah and I live in London');
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```
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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`).
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