How to use apple/aimv2-large-patch14-224-lit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="apple/aimv2-large-patch14-224-lit", trust_remote_code=True) 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, AutoModel processor = AutoProcessor.from_pretrained("apple/aimv2-large-patch14-224-lit", trust_remote_code=True) model = AutoModel.from_pretrained("apple/aimv2-large-patch14-224-lit", trust_remote_code=True)
How to use apple/aimv2-large-patch14-224-lit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir aimv2-large-patch14-224-lit apple/aimv2-large-patch14-224-lit
