Instructions to use felixw/itps-act with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use felixw/itps-act with LeRobot:
- Notebooks
- Google Colab
- Kaggle
metadata
library_name: lerobot
license: mit
tags:
- lerobot
- act
- robotics
- maze2d
- itps
- pytorch_model_hub_mixin
pipeline_tag: robotics
ITPS Maze2D — Action Chunking Transformer (ACT)
Pre-trained Action Chunking Transformer checkpoint used in Inference-Time Policy Steering through Human Interactions (paper, project page, code).
The model was trained on the D4RL Maze2D dataset and is intended to be loaded with the LeRobot policy classes.
Usage
Clone the inference repo, then load this checkpoint directly from the Hub:
git clone https://github.com/yanweiw/itps.git && cd itps
pip install -e .
python interact_maze2d.py -p act --hf
Or load it programmatically:
from itps.common.policies.act.modeling_act import ACTPolicy
policy = ACTPolicy.from_pretrained("felixw/itps-act")
policy.eval()
Citation
@article{wang2024itps,
title={Inference-Time Policy Steering through Human Interactions},
author={Wang, Yanwei and others},
journal={arXiv preprint arXiv:2411.16627},
year={2024}
}
License
MIT — see LICENSE.