Instructions to use Xenova/siglip-base-patch16-512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use Xenova/siglip-base-patch16-512 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('zero-shot-image-classification', 'Xenova/siglip-base-patch16-512');
Download onnx/text_model_quantized.onnx from Xenova/siglip-base-patch16-512: direct link, hf CLI and curl.
- Browser
- Download file 111 MB
-
https://huggingface.co/Xenova/siglip-base-patch16-512/resolve/main/onnx/text_model_quantized.onnx
- Command line
-
hf download hf://Xenova/siglip-base-patch16-512/onnx/text_model_quantized.onnx
-
curl -L -o text_model_quantized.onnx https://huggingface.co/Xenova/siglip-base-patch16-512/resolve/main/onnx/text_model_quantized.onnx
111 MB
- Xet hash:
- be4af374ca02beee6441abfd2e95c3908c799ab4bc305edb1cbc282cc37617fb
- Size of remote file:
- 111 MB
- SHA256:
- 4382445a30e786add98d9ccb601c6cfa89c07bb7e4972767b55a5404c71acc6e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.