README.md

---
library_name: lerobot
license: mit
tags:
  - lerobot
  - dp
  - robotics
  - maze2d
  - itps
  - pytorch_model_hub_mixin
pipeline_tag: robotics
---

# ITPS Maze2D — Diffusion Policy (DP)

Pre-trained Diffusion Policy 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 dp --hf
```

Or load it programmatically:

```python
from itps.common.policies.diffusion.modeling_diffusion import DiffusionPolicy

policy = DiffusionPolicy.from_pretrained("felixw/itps-dp")
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).