README.md

---
base_model: microsoft/table-transformer-structure-recognition-v1.1-all
library_name: transformers.js
---

https://huggingface.co/microsoft/table-transformer-structure-recognition-v1.1-all 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/@huggingface/transformers) using:
```bash
npm i @huggingface/transformers
```

**Example:** Run object-detection.

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

const detector = await pipeline('object-detection', 'Xenova/table-transformer-structure-recognition-v1.1-all');
const img = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg';
const output = await detector(img, { threshold: 0.9 });
```

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`).