Act Aloha Test is a model available on Hugging Face that implements Action Chunking with Transformers (ACT), an imitation learning approach for robotics. Below are 8 other ai apps with similar functionality to Act Aloha Test, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
act-hyak-test is an open-source imitation learning model for robotics, designed to predict action chunks from teleoperated data. It enables researchers and developers to run local inference and integrate advanced policy models into robotics workflows.
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_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.
act-record-test-test is an open-source imitation learning model for robotics, implementing action chunking with transformers. It enables developers to train and deploy policies that predict short action sequences from teleoperated data, improving robotic task performance.
So101-act-test is an open-source robotics model implementing action chunking with transformers for imitation learning. It predicts short action sequences from teleoperated data, supporting robotics research and development. Distributed via Hugging Face with open weights and documentation for integration.
act_policy_test4 is an open-source imitation-learning policy model designed for robotics applications, focusing on predicting short action chunks from teleoperated data. It can be integrated with LeRobot and other frameworks for training, evaluation, and deployment in robotics workflows. Ideal for robotics researchers and developers seeking ready-to-use policy models.
alohamini2test is an open-source imitation learning model for robotics, designed for the AlohaMini platform. It allows developers to train, evaluate, and deploy action chunking policies using the LeRobot library. The model is available on Hugging Face under an open license.
act_merged_all24 is an open-source imitation learning model designed for robotics applications, enabling prediction of short action chunks from teleoperated data. It is intended for robotics researchers and developers who want to train, evaluate, or deploy advanced action chunking policies. The model is available on Hugging Face under an open license and integrates with libraries like LeRobot.
