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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 683eee8e2a79e5dca1092e09ae5983946c05179f20795e3c6799c22c52fcbe45
- Size of remote file:
- 5.3 kB
- SHA256:
- bec9d58a64dadc29e65d1386918b7a95f913c50a3482e59530781dfc23885cb7
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