Spaces:
Running
title: HyperView
emoji: 🔮
colorFrom: purple
colorTo: blue
sdk: docker
app_port: 7860
pinned: false
HyperView — Imagenette (CLIP + HyCoCLIP)
This folder is the simplest copyable HyperView Space example in this repo. It keeps all dataset-specific settings in the constants block at the top of demo.py, so a coding agent can usually adapt it by editing one file.
This example runs HyperView with:
- CLIP embeddings (
openai/clip-vit-base-patch32) for Euclidean layout - HyCoCLIP embeddings (
hycoclip-vit-s) for Poincaré layout
The Docker image installs released HyperView packages from PyPI and precomputes the dataset, embeddings, and layouts during build for fast runtime startup.
Reuse This Template
When you copy this folder for your own dataset, change these parts first:
- Edit the constants block in demo.py.
- Rename the copied Space from
HyperViewto your own project name such asyourproject-HyperVieworHyperView-yourproject. - Update this README frontmatter, title, and H1.
- Point a deploy workflow at your new folder.
This starter currently installs hyperview==0.3.1 and hyper-models==0.1.0.
The defaults in demo.py are:
- Hugging Face dataset:
Multimodal-Fatima/Imagenette_validation - Split:
validation - Image field:
image - Label field:
label - Sample count:
300 - Layouts: CLIP + Euclidean, HyCoCLIP + Poincaré
If you only want one model in your own Space, keep a single entry in
EMBEDDING_LAYOUTS and delete the rest.
When contributing your own Space back to this repository, add a row to the
community table in the root README.md and include your Hugging Face Space ID
in the pull request description.
Build Model
The Dockerfile runs build_dataset() during image build. That means:
- the first expensive download/embedding pass happens at build time
- the runtime container mostly just launches HyperView
- there is no extra runtime configuration path to keep in sync
Deploy source
This folder is synchronized to Hugging Face Spaces by GitHub Actions from the
hyperview-spaces deployment repository.