Image Classification
Transformers
Safetensors
English
siglip
OpenSDI
Spotting Diffusion-Generated Images in the Open World
SDXL
AI-vs-Real
SigLIP2
Instructions to use prithivMLmods/OpenSDI-SDXL-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/OpenSDI-SDXL-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/OpenSDI-SDXL-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-SDXL-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/OpenSDI-SDXL-SigLIP2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e82ac0d01fad2786ea0dc292ddc10d4be3290b02237d46756dce961bcd5b182
- Size of remote file:
- 372 MB
- SHA256:
- bf36e1a50335a2a26dc81901fe09f9cb9327f6fbc86336e8fc078eb3e326a79b
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