Image Classification
Transformers
Safetensors
English
siglip
siglip2
384
explicit-content
adult-content
classification
Instructions to use prithivMLmods/siglip2-x256p32-explicit-content with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/siglip2-x256p32-explicit-content with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/siglip2-x256p32-explicit-content") 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/siglip2-x256p32-explicit-content") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/siglip2-x256p32-explicit-content") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a58edcd147f47728d4b7d24c876e6538955c32a1119d53c6f3d3b5a110d9e5d
- Size of remote file:
- 378 MB
- SHA256:
- 26fdf4b6b7d682bb4bad93cef5112ed0e59b003cecd8cfbe1859ee04b18bca06
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