Instructions to use google/siglip-base-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/siglip-base-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="google/siglip-base-patch16-224") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("google/siglip-base-patch16-224") model = AutoModelForZeroShotImageClassification.from_pretrained("google/siglip-base-patch16-224") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1882b4cdbba163350a020e94432ae6a9ddafa7f66e39b122f85c80cee9f942f
- Size of remote file:
- 813 MB
- SHA256:
- eb93f7f526b0a1b0e5f0612630f142bc5b6c05d329edff70478ff0a83e2bcd6e
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