Instructions to use prithivMLmods/SigLIP2-ImageShield-2n-large-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/SigLIP2-ImageShield-2n-large-256 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/SigLIP2-ImageShield-2n-large-256") 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-ImageShield-2n-large-256") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/SigLIP2-ImageShield-2n-large-256", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f3ac0dbc72ec3ed317a8beeb3def05f2022d738f8a2872ad046721faf51ba59
- Size of remote file:
- 2.43 GB
- SHA256:
- ea791b856e4d47865758c6fe9404ffcc02d7e1423713e4e1aaa6c55e88110cd3
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