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Xenova/clip-vit-large-patch14
clip-vit-large-patch14 is a zero-shot image classification model from Xenova. Use it for the zero-shot image classification task on the model card, and read the license before you ship it in a product. It is set up for transformers.js.
https://huggingface.co/openai/clip-vit-large-patch14 with ONNX weights to be compatible with Transformers.js.
Downloads · 30 days
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.onnx9.4 GB · 100%
From the Hugging Face model README
https://huggingface.co/openai/clip-vit-large-patch14 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 image classification.
import { pipeline } from '@huggingface/transformers';
const classifier = await pipeline('zero-shot-image-classification', 'Xenova/clip-vit-large-patch14');
const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/tiger.jpg';
const output = await classifier(url, ['tiger', 'horse', 'dog']);
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).