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"], )
# pip install -U transformers accelerate # 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", device_map="auto")
https://huggingface.co/google/siglip-large-patch16-384/resolve/refs%2Fpr%2F1/tokenizer.json
hf download hf://google/siglip-large-patch16-384@refs/pr/1/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/google/siglip-large-patch16-384/resolve/refs%2Fpr%2F1/tokenizer.json
