Instructions to use clfegg/image_embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use clfegg/image_embed with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-feature-extraction', 'clfegg/image_embed');
Download onnx/model_quantized.onnx from clfegg/image_embed: direct link, hf CLI and curl.
- Browser
- Download file 153 MB
-
https://huggingface.co/clfegg/image_embed/resolve/main/onnx/model_quantized.onnx
- Command line
-
hf download hf://clfegg/image_embed/onnx/model_quantized.onnx
-
curl -L -o model_quantized.onnx https://huggingface.co/clfegg/image_embed/resolve/main/onnx/model_quantized.onnx
153 MB
- Xet hash:
- 7553050bb60d07d82cdf235712763fa7180f505372bc867e5a55398044b9a04d
- Size of remote file:
- 153 MB
- SHA256:
- 0289057ec679d6b0de7cfcead09173eebffe5862c48873b09baa768a9668f520
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.