Dataset Viewer
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
files: list<item: struct<blob_sha1: string, path: string, sha256: string, size: int64>>
child 0, item: struct<blob_sha1: string, path: string, sha256: string, size: int64>
child 0, blob_sha1: string
child 1, path: string
child 2, sha256: string
child 3, size: int64
policy: struct<commit: string, contract_sha256: string, manifest_sha256: string, prefix: string, repo_id: st (... 34 chars omitted)
child 0, commit: string
child 1, contract_sha256: string
child 2, manifest_sha256: string
child 3, prefix: string
child 4, repo_id: string
child 5, run_id: string
child 6, step: int64
purpose: string
schema_version: int64
dataset: struct<repo: string, revision: string, modalities: list<item: string>, inventory_status: string>
child 0, repo: string
child 1, revision: string
child 2, modalities: list<item: string>
child 0, item: string
child 3, inventory_status: string
evaluation: struct<host: string, transport: string, cloud_evaluation_allowed: bool, gpu_observed: string, openpi (... 165 chars omitted)
child 0, host: string
child 1, transport: string
child 2, cloud_evaluation_allowed: bool
child 3, gpu_observed: string
child 4, openpi_root: string
child 5, behavior_root: string
child 6, checkpoint_source: string
child 7, normalization_source: string
child 8, reuse_radio_normalization: bool
child 9, milestone_updates: list<item: int64>
child 0, item: int64
training: struct<provider: string, platform: string, preset: string, cloud_gpu_limit: int64, preemptible: bool (... 301 chars omitted)
child 0, provider: string
child 1, platform: string
child 2, preset: string
child 3, cloud_gpu_limit: int64
child 4, preemptible: bool
child 5, max_elapsed_hours: int64
child 6, source_repo: string
child 7, source_revision: string
child 8, base_weights: string
child 9, task_count: int64
child 10, depth: bool
child 11, proposed_effective_batch: int64
child 12, proposed_updates: int64
child 13, peak_lr: double
child 14, warmup_updates: int64
child 15, end_lr: double
child 16, physical_batch_status: string
child 17, accumulation_status: string
hf_model_repo: string
private: bool
hf_rollout_repo: string
status: string
to
{'schema_version': Value('int64'), 'status': Value('string'), 'hf_model_repo': Value('string'), 'hf_rollout_repo': Value('string'), 'private': Value('bool'), 'training': {'provider': Value('string'), 'platform': Value('string'), 'preset': Value('string'), 'cloud_gpu_limit': Value('int64'), 'preemptible': Value('bool'), 'max_elapsed_hours': Value('int64'), 'source_repo': Value('string'), 'source_revision': Value('string'), 'base_weights': Value('string'), 'task_count': Value('int64'), 'depth': Value('bool'), 'proposed_effective_batch': Value('int64'), 'proposed_updates': Value('int64'), 'peak_lr': Value('float64'), 'warmup_updates': Value('int64'), 'end_lr': Value('float64'), 'physical_batch_status': Value('string'), 'accumulation_status': Value('string')}, 'evaluation': {'host': Value('string'), 'transport': Value('string'), 'cloud_evaluation_allowed': Value('bool'), 'gpu_observed': Value('string'), 'openpi_root': Value('string'), 'behavior_root': Value('string'), 'checkpoint_source': Value('string'), 'normalization_source': Value('string'), 'reuse_radio_normalization': Value('bool'), 'milestone_updates': List(Value('int64'))}, 'dataset': {'repo': Value('string'), 'revision': Value('string'), 'modalities': List(Value('string')), 'inventory_status': Value('string')}}
because column names don't match
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 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, 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 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
files: list<item: struct<blob_sha1: string, path: string, sha256: string, size: int64>>
child 0, item: struct<blob_sha1: string, path: string, sha256: string, size: int64>
child 0, blob_sha1: string
child 1, path: string
child 2, sha256: string
child 3, size: int64
policy: struct<commit: string, contract_sha256: string, manifest_sha256: string, prefix: string, repo_id: st (... 34 chars omitted)
child 0, commit: string
child 1, contract_sha256: string
child 2, manifest_sha256: string
child 3, prefix: string
child 4, repo_id: string
child 5, run_id: string
child 6, step: int64
purpose: string
schema_version: int64
dataset: struct<repo: string, revision: string, modalities: list<item: string>, inventory_status: string>
child 0, repo: string
child 1, revision: string
child 2, modalities: list<item: string>
child 0, item: string
child 3, inventory_status: string
evaluation: struct<host: string, transport: string, cloud_evaluation_allowed: bool, gpu_observed: string, openpi (... 165 chars omitted)
child 0, host: string
child 1, transport: string
child 2, cloud_evaluation_allowed: bool
child 3, gpu_observed: string
child 4, openpi_root: string
child 5, behavior_root: string
child 6, checkpoint_source: string
child 7, normalization_source: string
child 8, reuse_radio_normalization: bool
child 9, milestone_updates: list<item: int64>
child 0, item: int64
training: struct<provider: string, platform: string, preset: string, cloud_gpu_limit: int64, preemptible: bool (... 301 chars omitted)
child 0, provider: string
child 1, platform: string
child 2, preset: string
child 3, cloud_gpu_limit: int64
child 4, preemptible: bool
child 5, max_elapsed_hours: int64
child 6, source_repo: string
child 7, source_revision: string
child 8, base_weights: string
child 9, task_count: int64
child 10, depth: bool
child 11, proposed_effective_batch: int64
child 12, proposed_updates: int64
child 13, peak_lr: double
child 14, warmup_updates: int64
child 15, end_lr: double
child 16, physical_batch_status: string
child 17, accumulation_status: string
hf_model_repo: string
private: bool
hf_rollout_repo: string
status: string
to
{'schema_version': Value('int64'), 'status': Value('string'), 'hf_model_repo': Value('string'), 'hf_rollout_repo': Value('string'), 'private': Value('bool'), 'training': {'provider': Value('string'), 'platform': Value('string'), 'preset': Value('string'), 'cloud_gpu_limit': Value('int64'), 'preemptible': Value('bool'), 'max_elapsed_hours': Value('int64'), 'source_repo': Value('string'), 'source_revision': Value('string'), 'base_weights': Value('string'), 'task_count': Value('int64'), 'depth': Value('bool'), 'proposed_effective_batch': Value('int64'), 'proposed_updates': Value('int64'), 'peak_lr': Value('float64'), 'warmup_updates': Value('int64'), 'end_lr': Value('float64'), 'physical_batch_status': Value('string'), 'accumulation_status': Value('string')}, 'evaluation': {'host': Value('string'), 'transport': Value('string'), 'cloud_evaluation_allowed': Value('bool'), 'gpu_observed': Value('string'), 'openpi_root': Value('string'), 'behavior_root': Value('string'), 'checkpoint_source': Value('string'), 'normalization_source': Value('string'), 'reuse_radio_normalization': Value('bool'), 'milestone_updates': List(Value('int64'))}, 'dataset': {'repo': Value('string'), 'revision': Value('string'), 'modalities': List(Value('string')), 'inventory_status': Value('string')}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
BEHAVIOR pi0.5 all-100 rollouts
Public storage for videos and per-episode metrics from the all-100 experiment. Evaluation and replay run on the existing Linux machine, not Nebius.
No trained all-100 policy evaluation has been published yet. Every result must identify its policy commit, task, instance, seed, success, Q-score, steps and termination reason. Training replay and evaluation episodes remain separate.
Experiment plan and policies: behavior-pi05-all100.
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