Instructions to use google/siglip2-base-patch32-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/siglip2-base-patch32-256 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="google/siglip2-base-patch32-256") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("google/siglip2-base-patch32-256", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload processor
Browse files- preprocessor_config.json +1 -1
preprocessor_config.json
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"processor_class": "SiglipProcessor",
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"resample":
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"rescale_factor": 0.00392156862745098,
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"size": {
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"height": 256,
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"processor_class": "SiglipProcessor",
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"resample": 2,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"height": 256,
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