JosiahB5363/act_so101_piecetest715again is an open-source imitation-learning model for robotics, predicting short action chunks from teleoperated data. It helps researchers develop and evaluate robotic control policies using open weights and CLI tools.
Act So101 Piecetest715again sits in PulseGate's Other AI category. It focuses on enabling robotics researchers to use imitation learning for predicting action chunks in robotic control. It is built as an open-source project for robotics researchers and AI developers. Act So101 Piecetest715again is open source under the Apache-2.0 license. It runs on the web and the command line.
JosiahB5363 builds and maintains Act So101 Piecetest715again, and the product first shipped in 2024. Development happens publicly on GitHub with 25.8k stars and 157 commits in the last 90 days. Key capabilities include imitation learning, robotics policy prediction, and open source.
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