Image Classification
Transformers
Safetensors
English
siglip
OpenSDI
Spotting Diffusion-Generated Images in the Open World
AI-vs-Real
SigLIP2
SD2.1
Instructions to use prithivMLmods/OpenSDI-SD2.1-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/OpenSDI-SD2.1-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/OpenSDI-SD2.1-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-SD2.1-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/OpenSDI-SD2.1-SigLIP2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5168577925b370da302bbbf3b72eb1d5e747f460185cacf9b13fa5f17e081e1a
- Size of remote file:
- 372 MB
- SHA256:
- 02a01599aa7cdd11c97e431872b7c086dd3c19c7cd0d7bf0b73f39612a01273c
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