Instructions to use RabiatS/depth-anything-v2-small-web with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use RabiatS/depth-anything-v2-small-web with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('depth-estimation', 'RabiatS/depth-anything-v2-small-web');
Depth Anything V2, for the web
A copy of the ONNX files from onnx-community/depth-anything-v2-small at commit 4472b7362082ad9968fee890ca0f1e5aca36b93d, trimmed to the files that rabiatsadiq.com/lab loads in the browser. It lives here so the page can't change or disappear under it.
- Original model: Depth Anything V2, by Lihe Yang and team (HKU, TikTok), https://github.com/DepthAnything/Depth-Anything-V2
- Base weights: depth-anything/Depth-Anything-V2-Small-hf
- Licence: Apache 2.0, see LICENSE. The weights are unchanged.
- Downloads last month
- 29
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for RabiatS/depth-anything-v2-small-web
Base model
depth-anything/Depth-Anything-V2-Small-hf