It provides a comprehensive framework to build, train, and serve a JEPA‑driven world‑model agent, combining Python and Rust components. The repo includes data pipelines, encoders, dynamics, planners, and evaluation scripts, letting researchers experiment with self‑supervised world modeling and planning. It targets AI researchers and developers needing a ready‑to‑run agent stack, integrating deterministic NumPy and scalable PyTorch backends with Rust performance kernels. Compared to ad‑hoc prototypes, it offers a cohesive, reproducible environment with checkpointing, metrics, and modular architecture.
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