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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:    CastError
Message:      Couldn't cast
observation_state: fixed_size_list<item: float>[2]
  child 0, item: float
action: fixed_size_list<item: float>[2]
  child 0, item: float
episode_index: int64
frame_index: int64
timestamp: float
next_reward: float
next_done: bool
next_success: bool
index: int64
task_index: int64
to
{'path': Value('string'), 'data': Value('large_binary')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 489, 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 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, 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 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, 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/lance/lance.py", line 231, in _generate_tables
                  yield Key(frag_idx, batch_idx), self._cast_table(table)
                                                  ~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/lance/lance.py", line 188, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              observation_state: fixed_size_list<item: float>[2]
                child 0, item: float
              action: fixed_size_list<item: float>[2]
                child 0, item: float
              episode_index: int64
              frame_index: int64
              timestamp: float
              next_reward: float
              next_done: bool
              next_success: bool
              index: int64
              task_index: int64
              to
              {'path': Value('string'), 'data': Value('large_binary')}
              because column names don't match

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pusht, stored in Lance

lerobot/pusht converted to the Lance layout that LeRobot's LanceDBDataset reads natively. Same meta/ sidecar as the original, tabular features in frames.lance, encoded videos in a videos.lance blob v2 column.

from lerobot.datasets import LeRobotDataset  # not needed, shown for contrast
from lerobot.datasets import LanceDBDataset

ds = LanceDBDataset("lance-format/pusht-lance")  # streams tables from the Hub, only meta/ is downloaded
item = ds[0]

Or just point training at it. The dataset factory detects the format automatically:

lerobot-train --dataset.repo_id=lance-format/pusht-lance ...

Requires lancedb>=0.35.0b2 (pip install --pre --extra-index-url https://pypi.fury.io/lancedb/ lancedb) and the lance-dataloader branch of LeRobot until the upstream PR lands.

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