# D-JEPA: pusht-visual-shifts

- Architecture: `set_aligner`.
- Tensor count: 30.
- Includes pretrained predictor weights: false.
- Original checkpoint SHA256: `c9552d2ab5d477d5c07d71f64ac66a315f3bbcf287f866c40d64e857c67bac22`.
- Exported tensor-file SHA256: `cf36d6bd0af016d8adf2358d78feeda33c1bbf062eef1d0be6332ca1bb28f2e3`.

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: 3. Gate: `refined_gap`, strict threshold `0.01`; quantization decimals: `None`. Candidate IDs and feature preprocessing must match the task profile.

Project license is selected by the authors before public upload.