Image Classification
Transformers
Safetensors
English
siglip
OpenSDI
Spotting Diffusion-Generated Images in the Open World
SD1.5
AI-vs-Real
SigLIP2
Stable Diffusion v1-5
Instructions to use prithivMLmods/OpenSDI-SD1.5-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/OpenSDI-SD1.5-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/OpenSDI-SD1.5-SigLIP2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/OpenSDI-SD1.5-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/OpenSDI-SD1.5-SigLIP2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a6ee9ae1b832407ac80b9acdc56ab42d6a14c951f9114037986524dbd43c7b37
- Size of remote file:
- 372 MB
- SHA256:
- 1cbf1a92c45666035c1d684a1e28d66bf49a60ba5bcf3b0b154e0de5ac38e55a
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