import { pipeline } from '@xenova/transformers';

// Create image-to-text pipeline
const captioner = await pipeline('image-to-text', 'Xenova/trocr-base-handwritten');

// Perform optical character recognition
const image = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/handwriting.jpg';
const output = await captioner(image);
// [{ generated_text: 'Mr. Brown commented icily.' }]

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).