Action Chunking with Transformers (ACT)
is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high success rates.
This policy has been trained and pushed to the Hub using
LeRobot
.
See the full documentation at
LeRobot Docs
.
How to Get Started with the Model
For a complete walkthrough, see the
training guide
.
Below is the short version on how to train and run inference/eval:
pbw_v1_act huggingface.co is an AI model on huggingface.co that provides pbw_v1_act's model effect (), which can be used instantly with this doshima pbw_v1_act model. huggingface.co supports a free trial of the pbw_v1_act model, and also provides paid use of the pbw_v1_act. Support call pbw_v1_act model through api, including Node.js, Python, http.
pbw_v1_act huggingface.co is an online trial and call api platform, which integrates pbw_v1_act's modeling effects, including api services, and provides a free online trial of pbw_v1_act, you can try pbw_v1_act online for free by clicking the link below.
doshima pbw_v1_act online free url in huggingface.co:
pbw_v1_act is an open source model from GitHub that offers a free installation service, and any user can find pbw_v1_act on GitHub to install. At the same time, huggingface.co provides the effect of pbw_v1_act install, users can directly use pbw_v1_act installed effect in huggingface.co for debugging and trial. It also supports api for free installation.