---
library_name: transformers.js
---

https://huggingface.co/caidas/swin2SR-classical-sr-x4-64 with ONNX weights to be compatible with Transformers.js.

## Usage (Transformers.js)

If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@xenova/transformers) using:
```bash
npm i @xenova/transformers
```

**Example:** Upscale an image with `Xenova/swin2SR-classical-sr-x4-64`.
```js
import { pipeline } from '@xenova/transformers';

// Create image-to-image pipeline
const upscaler = await pipeline('image-to-image', 'Xenova/swin2SR-classical-sr-x4-64', {
    // quantized: false, // Uncomment this line to use the quantized version
});

// Upscale an image
const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/butterfly.jpg';
const output = await upscaler(url);
// RawImage {
//   data: Uint8Array(3145728) [ ... ],
//   width: 1024,
//   height: 1024,
//   channels: 3
// }

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

<details>
  <summary>See example output</summary>

  Input image:
  
  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/eqLyvsErNQvXAFDD2MylF.png)

  
  Output image:

  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/UUNNlHNQx1bRkK-0PxHPU.png)

</details>

---

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](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).