metadata
base_model: microsoft/table-transformer-structure-recognition
library_name: transformers.js
https://huggingface.co/microsoft/table-transformer-structure-recognition with ONNX weights to be compatible with Transformers.js.
Usage (Transformers.js)
If you haven't already, you can install the Transformers.js JavaScript library from NPM using:
npm i @huggingface/transformers
Example: Run object-detection.
import { pipeline } from '@huggingface/transformers';
const detector = await pipeline('object-detection', 'Xenova/table-transformer-structure-recognition');
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 and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).