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

// Create image-to-image pipeline
const upscaler = await pipeline('image-to-image', 'Xenova/2x_APISR_RRDB_GAN_generator-onnx', {
    dtype: "fp32",
});

// Upscale an image
const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/anime.png';
const output = await upscaler(url);
// RawImage {
//   data: Uint8Array(16588800) [ ... ],
//   width: 1280,
//   height: 960,
//   channels: 3
// }

// (Optional) Save the upscaled image
output.save('upscaled.png');

See example output

Input image:

Output image:

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).