Image Classification
Transformers
Safetensors
English
siglip
OpenSDI
Spotting Diffusion-Generated Images in the Open World
Flux.1
AI-vs-Real
SigLIP2
Instructions to use prithivMLmods/OpenSDI-Flux.1-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/OpenSDI-Flux.1-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/OpenSDI-Flux.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-Flux.1-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/OpenSDI-Flux.1-SigLIP2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ca9286749092fc563371096cf844e0dc9c63a5497458dc9a3ad2b73648c9ed9
- Size of remote file:
- 5.3 kB
- SHA256:
- 5ddb587f2e0557170aa6e5a866a23675974cbc6f0ada6180b0165721a997b3b2
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