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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
benchmark: string
evaluation_package: string
total_evaluations: int64
single_run_evaluations: int64
multi_run_evaluations: int64
unique_scenarios: int64
single_run: struct<hard_unstable_scenarios: int64, instability_rate_pct: double>
child 0, hard_unstable_scenarios: int64
child 1, instability_rate_pct: double
multi_run: struct<hard_unstable_scenarios: int64, instability_rate_pct: double, realized_executions_per_evaluat (... 11 chars omitted)
child 0, hard_unstable_scenarios: int64
child 1, instability_rate_pct: double
child 2, realized_executions_per_evaluation: int64
absolute_reduction_percentage_points: double
relative_reduction_pct: double
scope_note: string
false_continuation_decisions: int64
artifact_mismatches: int64
missing_score_cells: int64
tested_lifecycles: int64
correct_outcomes: int64
interpretation: string
false_convergence_decisions: int64
to
{'benchmark': Value('string'), 'tested_lifecycles': Value('int64'), 'correct_outcomes': Value('int64'), 'false_convergence_decisions': Value('int64'), 'false_continuation_decisions': Value('int64'), 'artifact_mismatches': Value('int64'), 'missing_score_cells': Value('int64'), 'interpretation': Value('string')}
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
benchmark: string
evaluation_package: string
total_evaluations: int64
single_run_evaluations: int64
multi_run_evaluations: int64
unique_scenarios: int64
single_run: struct<hard_unstable_scenarios: int64, instability_rate_pct: double>
child 0, hard_unstable_scenarios: int64
child 1, instability_rate_pct: double
multi_run: struct<hard_unstable_scenarios: int64, instability_rate_pct: double, realized_executions_per_evaluat (... 11 chars omitted)
child 0, hard_unstable_scenarios: int64
child 1, instability_rate_pct: double
child 2, realized_executions_per_evaluation: int64
absolute_reduction_percentage_points: double
relative_reduction_pct: double
scope_note: string
false_continuation_decisions: int64
artifact_mismatches: int64
missing_score_cells: int64
tested_lifecycles: int64
correct_outcomes: int64
interpretation: string
false_convergence_decisions: int64
to
{'benchmark': Value('string'), 'tested_lifecycles': Value('int64'), 'correct_outcomes': Value('int64'), 'false_convergence_decisions': Value('int64'), 'false_continuation_decisions': Value('int64'), 'artifact_mismatches': Value('int64'), 'missing_score_cells': Value('int64'), 'interpretation': 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.
Plumloom Evaluation Reliability Benchmark
Public results from Plumloom’s research on reliability in single-turn AI chat evaluations.
This dataset contains 45 controlled single-turn chat cases used to test whether repeated evaluation produces more stable model choices than one-shot evaluation. It also includes aggregate results from 38 measurement-reliability evaluation runs.
Private prompts, rubrics, model responses, and production execution details are intentionally excluded.
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