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Add/update the quantized ONNX model files and README.md for Transformers.js v3 (#2)
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---
base_model: MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli
library_name: transformers.js
pipeline_tag: zero-shot-classification
---
https://huggingface.co/MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli 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 classification.
```js
import { pipeline } from '@huggingface/transformers';
const classifier = await pipeline('zero-shot-classification', 'Xenova/DeBERTa-v3-large-mnli-fever-anli-ling-wanli');
const output = await classifier(
'I love transformers!',
['positive', 'negative']
);
```
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`).