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Xenova/nli-deberta-base
nli-deberta-base is a zero-shot classification model from Xenova. Use it when you need labels you did not train the model on. It is set up for transformers.js.
https://huggingface.co/cross-encoder/nli-deberta-base with ONNX weights to be compatible with Transformers.js.
Downloads · 30 days
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.onnx1.8 GB · 100%
From the Hugging Face model README
https://huggingface.co/cross-encoder/nli-deberta-base with ONNX weights to be compatible with Transformers.js.
If you haven't already, you can install the Transformers.js JavaScript library from NPM using:
npm i @huggingface/transformers
Example: Zero shot classification.
import { pipeline } from '@huggingface/transformers';
const classifier = await pipeline('zero-shot-classification', 'Xenova/nli-deberta-base');
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 and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).