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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
candidates: list<item: struct<iterations: list<item: int64>, metrics: struct<early_stop_probability_penalty: dou (... 176 chars omitted)
child 0, item: struct<iterations: list<item: int64>, metrics: struct<early_stop_probability_penalty: double, early_ (... 164 chars omitted)
child 0, iterations: list<item: int64>
child 0, item: int64
child 1, metrics: struct<early_stop_probability_penalty: double, early_stop_rate: double, naturalness: double, output_ (... 60 chars omitted)
child 0, early_stop_probability_penalty: double
child 1, early_stop_rate: double
child 2, naturalness: double
child 3, output_entropy: double
child 4, output_entropy_mean: double
child 5, total: double
child 2, rank: list<item: double>
child 0, item: double
child 3, token_ids: list<item: int64>
child 0, item: int64
constraint_tolerance: double
deduplicated_snapshot_occurrences: int64
protocol: string
selected_iteration: int64
selected_token_ids: list<item: int64>
child 0, item: int64
snapshot_interval: int64
unique_snapshot_count: int64
unique_hard_candidate_count: int64
snapshots: list<item: struct<step: int64, suffix_min_pmax_at_temperature_end: double, token_ids: list<item: int (... 42 chars omitted)
child 0, item: struct<step: int64, suffix_min_pmax_at_temperature_end: double, token_ids: list<item: int64>, valida (... 30 chars omitted)
child 0, step: int64
child 1, suffix_min_pmax_at_temperature_end: double
child 2, token_ids: list<item: int64>
child 0, item: int64
child 3, validation_rank: list<item: double>
child 0, item: double
selected_step: int64
selected_rank: list<item: double>
child 0, item: double
feasibility_tolerance: double
snapshot_count: int64
selection_policy: string
unique_candidates: list<item: struct<exact_metrics: struct<early_stop_probability_penalty: double, early_stop_rate: dou (... 125 chars omitted)
child 0, item: struct<exact_metrics: struct<early_stop_probability_penalty: double, early_stop_rate: double, natura (... 113 chars omitted)
child 0, exact_metrics: struct<early_stop_probability_penalty: double, early_stop_rate: double, naturalness: double, output_ (... 60 chars omitted)
child 0, early_stop_probability_penalty: double
child 1, early_stop_rate: double
child 2, naturalness: double
child 3, output_entropy: double
child 4, output_entropy_mean: double
child 5, total: double
child 1, token_ids: list<item: int64>
child 0, item: int64
to
{'feasibility_tolerance': Value('float64'), 'selected_rank': List(Value('float64')), 'selected_step': Value('int64'), 'selected_token_ids': List(Value('int64')), 'selection_policy': Value('string'), 'snapshot_count': Value('int64'), 'snapshots': List({'step': Value('int64'), 'suffix_min_pmax_at_temperature_end': Value('float64'), 'token_ids': List(Value('int64')), 'validation_rank': List(Value('float64'))}), 'unique_candidates': List({'exact_metrics': {'early_stop_probability_penalty': Value('float64'), 'early_stop_rate': Value('float64'), 'naturalness': Value('float64'), 'output_entropy': Value('float64'), 'output_entropy_mean': Value('float64'), 'total': Value('float64')}, 'token_ids': List(Value('int64'))}), 'unique_hard_candidate_count': Value('int64')}
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/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 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
candidates: list<item: struct<iterations: list<item: int64>, metrics: struct<early_stop_probability_penalty: dou (... 176 chars omitted)
child 0, item: struct<iterations: list<item: int64>, metrics: struct<early_stop_probability_penalty: double, early_ (... 164 chars omitted)
child 0, iterations: list<item: int64>
child 0, item: int64
child 1, metrics: struct<early_stop_probability_penalty: double, early_stop_rate: double, naturalness: double, output_ (... 60 chars omitted)
child 0, early_stop_probability_penalty: double
child 1, early_stop_rate: double
child 2, naturalness: double
child 3, output_entropy: double
child 4, output_entropy_mean: double
child 5, total: double
child 2, rank: list<item: double>
child 0, item: double
child 3, token_ids: list<item: int64>
child 0, item: int64
constraint_tolerance: double
deduplicated_snapshot_occurrences: int64
protocol: string
selected_iteration: int64
selected_token_ids: list<item: int64>
child 0, item: int64
snapshot_interval: int64
unique_snapshot_count: int64
unique_hard_candidate_count: int64
snapshots: list<item: struct<step: int64, suffix_min_pmax_at_temperature_end: double, token_ids: list<item: int (... 42 chars omitted)
child 0, item: struct<step: int64, suffix_min_pmax_at_temperature_end: double, token_ids: list<item: int64>, valida (... 30 chars omitted)
child 0, step: int64
child 1, suffix_min_pmax_at_temperature_end: double
child 2, token_ids: list<item: int64>
child 0, item: int64
child 3, validation_rank: list<item: double>
child 0, item: double
selected_step: int64
selected_rank: list<item: double>
child 0, item: double
feasibility_tolerance: double
snapshot_count: int64
selection_policy: string
unique_candidates: list<item: struct<exact_metrics: struct<early_stop_probability_penalty: double, early_stop_rate: dou (... 125 chars omitted)
child 0, item: struct<exact_metrics: struct<early_stop_probability_penalty: double, early_stop_rate: double, natura (... 113 chars omitted)
child 0, exact_metrics: struct<early_stop_probability_penalty: double, early_stop_rate: double, naturalness: double, output_ (... 60 chars omitted)
child 0, early_stop_probability_penalty: double
child 1, early_stop_rate: double
child 2, naturalness: double
child 3, output_entropy: double
child 4, output_entropy_mean: double
child 5, total: double
child 1, token_ids: list<item: int64>
child 0, item: int64
to
{'feasibility_tolerance': Value('float64'), 'selected_rank': List(Value('float64')), 'selected_step': Value('int64'), 'selected_token_ids': List(Value('int64')), 'selection_policy': Value('string'), 'snapshot_count': Value('int64'), 'snapshots': List({'step': Value('int64'), 'suffix_min_pmax_at_temperature_end': Value('float64'), 'token_ids': List(Value('int64')), 'validation_rank': List(Value('float64'))}), 'unique_candidates': List({'exact_metrics': {'early_stop_probability_penalty': Value('float64'), 'early_stop_rate': Value('float64'), 'naturalness': Value('float64'), 'output_entropy': Value('float64'), 'output_entropy_mean': Value('float64'), 'total': Value('float64')}, 'token_ids': List(Value('int64'))}), 'unique_hard_candidate_count': Value('int64')}
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.
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