# D-JEPA: granular-multiview

- Architecture: `granular`.
- Tensor count: 30.
- Includes pretrained predictor weights: false.
- Original checkpoint SHA256: `e796fa3ee2fbc6f5b4abdfae99e8fa843606f923284a7fb95f59c0fc6c512c70`.
- Exported tensor-file SHA256: `2ee5783def21816054645f87d9cffa50900733b7218a2b9ee203ae39aec682ff`.

Load `model.pt` with `torch.load(..., map_location="cpu", weights_only=True)`. Use the matching D-JEPA code profile and JSON configuration. Tensor values are unchanged; metadata and optimizer state have been separated.

Input width: 4. Gate: `base_minus_refined`, strict threshold `-0.010684727949480862`; quantization decimals: `None`. Candidate IDs and feature preprocessing must match the task profile.

Project license is selected by the authors before public upload.