A model zoo for non-Euclidean embedding models
Hyperbolic · Spherical · Product Manifolds
- Standardized access to non-Euclidean embedding models
- Torch-free runtime via ONNX (models published to Hugging Face Hub)
- Simple API —
load()andencode_images()
pip install hyper-modelsimport 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)| Model | Available | Paper | Code |
|---|---|---|---|
hycoclip-vit-s |
ICLR 2025 | PalAvik/hycoclip | |
hycoclip-vit-b |
ICLR 2025 | PalAvik/hycoclip | |
meru-vit-s |
ICML 2023 | facebookresearch/meru | |
meru-vit-b |
ICML 2023 | facebookresearch/meru | |
hyp-vit |
— | CVPR 2022 | htdt/hyp_metric |
hie |
— | CVPR 2020 | leymir/hyperbolic-image-embeddings |
hcnn |
— | ICLR 2024 | kschwethelm/HyperbolicCV |
| Model | Available | Paper | Code |
|---|---|---|---|
megadescriptor |
WACV 2024 | WildlifeDatasets/wildlife-datasets | |
sphereface |
— | CVPR 2017 | wy1iu/sphereface |
arcface |
— | CVPR 2019 | deepinsight/insightface |
| Model | Available | Paper | Code |
|---|---|---|---|
hyperbolics |
— | ICLR 2019 | HazyResearch/hyperbolics |
This repo also contains tooling to export PyTorch models to ONNX:
cd export/hycoclip
uv run python export_onnx.py --checkpoint model.pth --onnx model.onnxSee export/hycoclip/README.md for details.