它引入了一个记忆增强的高层策略，结合大规模低层策略（基于 40,115 小时异构真实世界机器人数据训练），并通过世界模型进行测试时推理，且完全开源。
This repo is the official implementation of "τ0-VLA: a Hierarchical Robot Foundation Model with World-Model-Guided Test-Time Computation".
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