https://huggingface.co/OFA-Sys/chinese-clip-vit-large-patch14-336px with ONNX weights to be compatible with Transformers.js.
Usage (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/chinese-clip-vit-large-patch14-336px');
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 ๐ค Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named onnx
).
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