granular-multiview/README.md

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.