act_so101_test is an open-source imitation-learning model for robotics, focusing on action chunking and policy inference. It is designed for robotics researchers and developers to train and evaluate robotic policies using open weights and Python integration.
Act So101 Test is an Other AI product. It focuses on providing an open-source model for robotics imitation learning and action chunking to improve policy inference. It is built as an open-source project for robotics researchers and developers. Act So101 Test is open source under the Apache-2.0 license. Act So101 Test is available on the web and the command line, and it can be self-hosted.
It is developed by jgreeley, and the product first shipped in 2024. Development happens publicly on GitHub with 25.8k stars and 157 commits in the last 90 days. PulseGate's similarity index finds few close equivalents — Act So101 Test occupies a relatively distinct niche. Key capabilities include imitation learning, robotics policy, and action chunking.
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