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
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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](https://huggingface.co/papers/2411.16627), [project page](https://yanweiw.github.io/itps/), [code](https://github.com/yanweiw/itps)).
The model was trained on the [D4RL Maze2D](https://github.com/Farama-Foundation/D4RL)
dataset and is intended to be loaded with the
[LeRobot](https://github.com/huggingface/lerobot) policy classes.
## Usage
Clone the inference repo, then load this checkpoint directly from the Hub:
```bash
git clone https://github.com/yanweiw/itps.git && cd itps
pip install -e .
python interact_maze2d.py -p act --hf
```
Or load it programmatically:
```python
from itps.common.policies.act.modeling_act import ACTPolicy
policy = ACTPolicy.from_pretrained("felixw/itps-act")
policy.eval()
```
## Citation
```bibtex
@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](https://github.com/yanweiw/itps/blob/main/LICENSE).
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