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zzsi/swm-dmc-expert

swm-dmc-expert Expert demonstration dataset for DeepMind Control Suite environments, repacked from the galilai-group/stable-worldmodel release. Files File Description dmc_expert.tar.zst Zstd-compressed tarball of expert trajectories; internal paths are dmc/expert/<env>/run.h5 Format Each run.h5 is an HDF5 file (Blosc-compressed) with datasets: Key Shape Description pixels (N, 224, 224, 3) uint8 RGB frames, 224×224 action… See the full description on the dataset page: https://huggingface.co/datasets/zzsi/swm-dmc-expert.

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swm-dmc-expert

Expert demonstration dataset for DeepMind Control Suite environments, repacked from the galilai-group/stable-worldmodel release.

Files

File	Description
`dmc_expert.tar.zst`	Zstd-compressed tarball of expert trajectories; internal paths are `dmc/expert/<env>/run.h5`

Format

Each run.h5 is an HDF5 file (Blosc-compressed) with datasets:

Key	Shape	Description
`pixels`	`(N, 224, 224, 3)` uint8	RGB frames, 224×224
`action`	`(N, 6)` float32	DMControl action at each step
`ep_offset`	`(E,)` int	Start index of each episode
`ep_len`	`(E,)` int	Length of each episode

Requires hdf5plugin (Blosc filter) to read: import hdf5plugin, h5py.

Source

—Upstream repo: https://github.com/galilai-group/stable-worldmodel
—Original split: expert from dmc.tar.zst

Citation

If you use these artifacts, please cite the original work:

bibtex

@misc{maes_lelidec2026swm-1,
      title={stable-worldmodel-v1: Reproducible World Modeling Research and Evaluation},
      author={Lucas Maes and Quentin Le Lidec and Dan Haramati and
              Nassim Massaudi and Damien Scieur and Yann LeCun and
              Randall Balestriero},
      year={2026},
      eprint={2602.08968},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2602.08968},
}