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")
