import hyper_models from PIL import Image # List available models hyper_models.list_models() # ['hycoclip-vit-s', 'hycoclip-vit-b', 'meru-vit-s', 'meru-vit-b'] # Load model (auto-downloads from Hugging Face Hub) model = hyper_models.load("hycoclip-vit-s") model.geometry # 'hyperboloid' model.dim # 513 # Encode PIL images images = [Image.open("image.jpg")] embeddings = model.encode_images(images) # (1, 513) ndarray # Get model info info = hyper_models.get_model_info("hycoclip-vit-s") info.hub_id # 'mnm-matin/hyperbolic-clip' info.license # 'CC-BY-NC' # Low-level: preprocess images yourself batch = hyper_models.preprocess_images(images) # (B, 3, 224, 224) embeddings = model.encode(batch)