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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    ValueError
Message:      Dataset 'ep_len' has length 200 but expected 95962
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 76, in _generate_tables
                  num_rows = _check_dataset_lengths(h5, self.info.features)
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 353, in _check_dataset_lengths
                  raise ValueError(f"Dataset '{path}' has length {dset.shape[0]} but expected {num_rows}")
              ValueError: Dataset 'ep_len' has length 200 but expected 95962

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.

LeWAM Tool Hang — two views

Simulation training data used by LeWAM.

  • Episodes: 200
  • Frames: 95,962
  • Camera columns: pixels, pixels_r0eih
  • Action dimensions: 7

Files

File Bytes Purpose
toolhang.h5 5,030,456,346 Scene camera, actions and episode metadata
toolhang_eih.h5 4,622,226,254 Wrist-camera supplement
toolhang_multiview.h5 2,500 Portable multiview entry point; requires both companion HDF5 files

Tool Hang has two recorded cameras (scene and wrist). This dataset does not contain a third camera.

Download the entire repository and keep the HDF5 files together. The multiview entry point uses relative HDF5 links to its companion files; it contains no cluster-specific paths. Open toolhang_multiview.h5 for all views.

Download and read

pip install huggingface_hub h5py hdf5plugin
from pathlib import Path
from huggingface_hub import snapshot_download
import hdf5plugin  # registers the image compression filters
import h5py

root = Path(snapshot_download("LeWAM/lewam-toolhang-2view", repo_type="dataset"))
with h5py.File(root / "toolhang_multiview.h5", "r") as data:
    print(list(data.keys()))
    image = data["pixels"][0]
    action = data["action"][0]

Integrity and format

manifest.json records the byte size and SHA-256 of every HDF5 file. Camera frames are 224 × 224 RGB. ep_offset and ep_len describe episode boundaries. No optional preload cache is required.

The companion data files preserve the source training data bytes. Multiview entry points only combine columns; no trajectories or camera views are synthesized.

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