Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 81, in _split_generators
                  first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE))
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
                  fs: fsspec.AbstractFileSystem = fsspec.filesystem("memory")
                                                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 302, in filesystem
                  cls = get_filesystem_class(protocol)
                File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 239, in get_filesystem_class
                  raise ValueError(f"Protocol not known: {protocol}")
              ValueError: Protocol not known: memory
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 71, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

GLAM Datasets

Heterogeneous manipulation demonstrations for GLAM: Imitation from Heterogeneous Demonstrations using Grounded Latent-Action World Models (project page · code).

Each task combines a small target set — action-labelled demonstrations on our dual-arm Kinova robot (Frank) in MuJoCo — with a larger, action-free auxiliary set collected by a floating UMI gripper, also in MuJoCo.

Contents

Archive Task Episodes Size
stack_two.tar task 1 — stack two cubes (single arm) 500 UMI + 500 Frank 29 GB
stack_three.tar task 2 — stack three cubes (dual arm) 500 UMI + 200 Frank 31 GB

Each episode folder contains the trajectory (*.npz: poses, joints, actions), raw RGB frames from two cameras (front_frames/, overhead_frames/), and the corresponding object masks (*_frames_mask/).

Usage

pip install -U huggingface_hub
hf download VVVVVVVVIC/glam-datasets --repo-type dataset --local-dir data/
tar -xf data/stack_two.tar -C data/ && rm data/stack_two.tar
tar -xf data/stack_three.tar -C data/ && rm data/stack_three.tar

This produces data/stack_two/{umi,frank}/task_01/... and data/stack_three/{umi,frank}/task_02/..., ready for the training commands in the GLAM repository.

Citation

@article{wang2026imitation,
  title={Imitation from Heterogeneous Demonstrations using Grounded Latent-Action World Models},
  author={Wang, Tianyou and Lei, Anson and Watson, Joe and Posner, Ingmar},
  journal={arXiv preprint arXiv:2606.21672},
  year={2026}
}
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