Image Classification
Transformers
Safetensors
English
siglip
siglip2
256
patch16
adult-content-detection
explicit-content-detection
Instructions to use prithivMLmods/siglip2-x256-explicit-content with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/siglip2-x256-explicit-content with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/siglip2-x256-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-x256-explicit-content") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/siglip2-x256-explicit-content", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a01f68ba72a3331576d00653dddd90f8768503ddaf105fb96f4f22e0802c1a39
- Size of remote file:
- 5.3 kB
- SHA256:
- 77f0ca87b3994c04b4f018469a0d2842d64d1c9897f79e494161c2d4afdb6510
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