metadata
base_model: Intel/dpt-large
library_name: transformers.js
https://huggingface.co/Intel/dpt-large 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: Depth estimation.
import { pipeline } from '@huggingface/transformers';
const depth_estimator = await pipeline('depth-estimation', 'Xenova/dpt-large');
const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg';
const out = await depth_estimator(url);
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).