This Hugging Face model provides an imitation-learning policy for robotics, predicting action chunks from teleoperated data. Below are 7 other ai apps with similar functionality to Act Top Down 50 Augmentation, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
act_slow is an open-source robotics model that implements action chunking with transformers for imitation learning. It is designed for robotics researchers and developers who want to train and deploy advanced policies for robotic control tasks.
topright-act is a transformer-based imitation-learning policy model for robotics, focused on action chunking. It allows robotics researchers and developers to implement and experiment with advanced policy learning techniques using open-source weights and documentation.
act_DS3_1B1O_FV_removeidle_rand20 is an open-source model for robotic action chunking using imitation learning. It enables robotics researchers to implement and evaluate action chunking policies for efficient robot control.
act_task1_v2 is an open-source imitation learning policy for robotics, trained to predict action chunks from teleoperated data. It is designed for use with LeRobot and supports local inference and further training by robotics researchers and engineers.
kob0105/act_pusht is an open-source imitation-learning model for robotics, designed to predict short action chunks from teleoperated data. It is available on Hugging Face for use in research and development, supporting integration with LeRobot and Colab.
act_so101_grasp_50_v2 is an open-source robotics model implementing Action Chunking with Transformers (ACT) for imitation learning. It predicts short action chunks from teleoperated data, helping robotics researchers and developers train and evaluate robotic policies efficiently. The model is available for use via Hugging Face and integrates with tools like LeRobot.
topright-act is an open-source robotics policy model implementing action chunking with transformers. It integrates with the LeRobot framework and is suitable for robotics researchers and developers seeking advanced imitation-learning solutions for automation tasks.
