Image Classification
Transformers
Safetensors
English
siglip
Image-Classification
Watermark-Detection
SigLIP2
Instructions to use prithivMLmods/Watermark-Detection-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Watermark-Detection-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Watermark-Detection-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/Watermark-Detection-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Watermark-Detection-SigLIP2") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8da955f4503771c86722a9483e999f5f505e8d516e26d72e87c49f7e39c60ddd
- Size of remote file:
- 5.3 kB
- SHA256:
- 4138dcb234dcef0352a6fbae254152fc6e7544045ab1dbc0e451ec4366da1634
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