Instructions to use google/siglip-large-patch16-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/siglip-large-patch16-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="google/siglip-large-patch16-384") 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-large-patch16-384") model = AutoModelForZeroShotImageClassification.from_pretrained("google/siglip-large-patch16-384") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7ba3beb9fd7d5b70c1a6224637a5c73af401aaf795d1917101d62da95af990c
- Size of remote file:
- 2.61 GB
- SHA256:
- ab804d2c2c631159f65afa1de27787c5dba90cbfa189f26404de1944d50a18a2
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