How to use pulsejet/siglip-base-patch16-256-multilingual-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="pulsejet/siglip-base-patch16-256-multilingual-onnx") 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("pulsejet/siglip-base-patch16-256-multilingual-onnx") model = AutoModelForZeroShotImageClassification.from_pretrained("pulsejet/siglip-base-patch16-256-multilingual-onnx")
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