How to use mlx-community/siglip2-so400m-patch16-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="mlx-community/siglip2-so400m-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 AutoModel model = AutoModel.from_pretrained("mlx-community/siglip2-so400m-patch16-384", dtype="auto")
How to use mlx-community/siglip2-so400m-patch16-384 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir siglip2-so400m-patch16-384 mlx-community/siglip2-so400m-patch16-384
