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---
license: gpl-3.0
library_name: transformers.js
tags:
- apisr
- super-resolution
pipeline_tag: image-to-image
---
https://github.com/Kiteretsu77/APISR 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/4x_APISR_GRL_GAN_generator-onnx`.
```js
import { pipeline } from '@xenova/transformers';
// Create image-to-image pipeline
const upscaler = await pipeline('image-to-image', 'Xenova/4x_APISR_GRL_GAN_generator-onnx', {
quantized: false,
});
// 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: 2560,
// height: 1920,
// channels: 3
// }
// (Optional) Save the upscaled image
output.save('upscaled.png');
```
<details>
<summary>See example output</summary>
Input image:
Output image:
</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`). |