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/vision_model_quantized.onnx from Xenova/siglip-base-patch16-512: direct link, hf CLI and curl.
- Browser
- Download file 100 MB
-
https://huggingface.co/Xenova/siglip-base-patch16-512/resolve/main/onnx/vision_model_quantized.onnx
- Command line
-
hf download hf://Xenova/siglip-base-patch16-512/onnx/vision_model_quantized.onnx
-
curl -L -o vision_model_quantized.onnx https://huggingface.co/Xenova/siglip-base-patch16-512/resolve/main/onnx/vision_model_quantized.onnx
100 MB
- Xet hash:
- 3be62690a9b042d19dbebd20d892ae66b3d63daa06579fa012e5e62696979fdc
- Size of remote file:
- 100 MB
- SHA256:
- f11f98b37629e56659ae6ae00a881d0153f4c08368c539f8e3b9dec0f8ae5e1a
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