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fix readme pt 3

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@ -38,6 +38,6 @@ The two important hyperparameters are the size of the latent vector (dim) and th
I think this probably will contribute significantly to solving continual learning and memory but I still need other people to review and verify my work! Please feel free to open GitHub issues to tell me what's wrong. If you have compute (e.g. you are a lab), feel free to fork my code and train larger models as well, with credit. I think this probably will contribute significantly to solving continual learning and memory but I still need other people to review and verify my work! Please feel free to open GitHub issues to tell me what's wrong. If you have compute (e.g. you are a lab), feel free to fork my code and train larger models as well, with credit.
Below is an approximate flow chart of the model architecture, made in Apple's Freeform app (excluding the wrapper for dataset cleaning and input/output handling) for reference. Below is an approximate flow chart of the model architecture, made in Apple's Freeform app (excluding the wrapper for dataset cleaning and input/output handling) for reference. Note that the arrow connecting the target latent to the CE loss should instead be the target byte to the CE loss.
<img width="1653" height="1161" alt="JEPA thing" src="https://github.com/user-attachments/assets/2d3a34ff-ba6a-44b8-b361-6c73da9216c0" /> <img width="1653" height="1161" alt="JEPA thing" src="https://github.com/user-attachments/assets/2d3a34ff-ba6a-44b8-b361-6c73da9216c0" />