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These are trained DeepStarNoodles weights (StarSeg, Hydra, Noodle Tracer). Access is gated so we know who has the locked recipe. DINOv3 backbone weights are not included; download those from Meta under the DINOv3 License.
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DeepStarNoodles weights
Locked inference and retrain weights for DeepStarNoodles.
| File | Role | SHA-256 |
|---|---|---|
starseg/starseg_best.pt |
StarSeg detector (YOLOv8) | 0252e49d3b201f5fe557536d37648ff6ff8ac1ca2c303ec7b5c707f1973a9414 |
hydra/epoch_060.pt |
18-channel Hydra parent | b3423e9bab886777e04825945434b8d42609b3c3fde0cd270d2fe2668c411eec |
hydra/endpoint_mse_best.pt |
Released dense Hydra | dcf7140c9ef0129d8f66b33b05af6d0ebb064f84b41ce61e51e67061799e3f02 |
tracer/noodle_tracer_seed20260807_endpoint_mse_calibrated.pt |
Noodle Tracer | bb7f1b5da4f998006163b0bfbba005b417dfd6e8ab313d8e3869b7224fcc5c6c |
First-party weights are MIT, matching the GitHub code. StarSeg inference uses Ultralytics (AGPL-3.0). The DINOv3 ConvNeXt-Base backbone is not in this repo; get dinov3_convnext_base_pretrain_lvd1689m-801f2ba9.pth from Meta (SHA-256 801f2ba95801bdcc9a8b77e293d38b35b355dbc813ef609cd82e18c3a185e8da).
Download into a DeepStarNoodles checkout
hf download weertman/deepstarnoodles --local-dir MODELS
Then place the Meta DINOv3 file at MODELS/dinov3/dinov3_convnext_base_pretrain_lvd1689m-801f2ba9.pth and run SCRIPTS/validate_artifacts.py.