HoloD3 model artifacts
This private model repository stores the exact PyTorch checkpoints used by the
HoloD3 reproduction package. The source code, annotations, training inputs, and
artifact manifests live in the private GitHub repository. Model paths in this
repository intentionally match their checkout locations under models/.
Download
First obtain read access to this private model repository. Authenticate without placing a token in a command-line argument:
uv run hf auth login
From a HoloD3 checkout, download only the four operational checkpoints:
uv run holod3 fetch-models --scope production
uv run holod3 verify
Download the production checkpoints plus the exact YOLO training initializers:
uv run holod3 fetch-models --scope reproduction
Download all 17 archived production, initializer, baseline, retrained, and comparison checkpoints:
uv run holod3 fetch-models --scope all
scripts/fetch_models.py exposes the same operation for users who prefer a
script entry point. Every downloaded file is checked against its recorded byte
size and SHA-256 digest in models/remote_manifest.json.
Production chain
| Stage | Checkpoint |
|---|---|
| MinIP particle detection | models/production/yolo/best.pt |
| Primary depth scoring | models/production/depth/depth_compare_robust_v1.pt |
| Routed depth fallback | models/production/depth/depth_compare_best.pt |
| Combined diameter estimation | models/production/diameter/slice_diammodel_best.pt |
The production rules, thresholds, provenance, and hashes are recorded in
models/production/manifest.json. See the GitHub repository's
docs/model-card.md, docs/parity.md, and docs/training.md for the intended
domain, limitations, exact fallback rules, and complete retraining procedure.
Access and licensing
This repository is private because no public redistribution license has been selected for the project-specific checkpoints or training data. The production YOLO checkpoint contains Ultralytics AGPL-3.0 metadata. Access does not grant permission to redistribute artifacts; consult the repository owner and the notices in the source repository before deployment or redistribution.