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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
BLOWJOB: struct<id: string, model: string, name: string, label: string, lora: struct<high: struct<lora_name: (... 207 chars omitted)
child 0, id: string
child 1, model: string
child 2, name: string
child 3, label: string
child 4, lora: struct<high: struct<lora_name: string, tams_lora_name: string, strength_model: int64>, low: struct<l (... 65 chars omitted)
child 0, high: struct<lora_name: string, tams_lora_name: string, strength_model: int64>
child 0, lora_name: string
child 1, tams_lora_name: string
child 2, strength_model: int64
child 1, low: struct<lora_name: string, tams_lora_name: string, strength_model: int64>
child 0, lora_name: string
child 1, tams_lora_name: string
child 2, strength_model: int64
child 5, prompts: struct<Kneeling: struct<prompt: string, description: string>>
child 0, Kneeling: struct<prompt: string, description: string>
child 0, prompt: string
child 1, description: string
LYING_BJ: struct<id: string, model: string, name: string, label: string, lora: struct<high: struct<lora_name: (... 209 chars omitted)
child 0, id: string
child 1, model: string
child 2, name: string
child 3, label: string
child 4, lora: struct<high: struct<lora_name: string, tams_lora_name: string, strength_model: int64>, low: struct<l (... 65 chars omitted)
child 0, high: struct<lora_name: string, tams_lora_name: string, strength_model: int64>
ch
...
ild 5, emotional_breakdown: bool
child 3, steps: int64
BLOW: struct<version: int64, name: string, cuts: list<item: struct<lora: string, duration: int64, trim_fra (... 97 chars omitted)
child 0, version: int64
child 1, name: string
child 2, cuts: list<item: struct<lora: string, duration: int64, trim_frames: int64, prompt_name: string, universal_ (... 39 chars omitted)
child 0, item: struct<lora: string, duration: int64, trim_frames: int64, prompt_name: string, universal_lora: bool, (... 27 chars omitted)
child 0, lora: string
child 1, duration: int64
child 2, trim_frames: int64
child 3, prompt_name: string
child 4, universal_lora: bool
child 5, emotional_breakdown: bool
child 3, steps: int64
RBLOWMOUTH: struct<version: int64, name: string, cuts: list<item: struct<lora: string, prompt_name: string, dura (... 97 chars omitted)
child 0, version: int64
child 1, name: string
child 2, cuts: list<item: struct<lora: string, prompt_name: string, duration: int64, trim_frames: int64, universal_ (... 39 chars omitted)
child 0, item: struct<lora: string, prompt_name: string, duration: int64, trim_frames: int64, universal_lora: bool, (... 27 chars omitted)
child 0, lora: string
child 1, prompt_name: string
child 2, duration: int64
child 3, trim_frames: int64
child 4, universal_lora: bool
child 5, emotional_breakdown: bool
child 3, steps: int64
to
{'BLOW': {'version': Value('int64'), 'name': Value('string'), 'cuts': List({'lora': Value('string'), 'duration': Value('int64'), 'trim_frames': Value('int64'), 'prompt_name': Value('string'), 'universal_lora': Value('bool'), 'emotional_breakdown': Value('bool')}), 'steps': Value('int64')}, 'RBLOW': {'version': Value('int64'), 'name': Value('string'), 'cuts': List({'lora': Value('string'), 'prompt_name': Value('string'), 'duration': Value('int64'), 'trim_frames': Value('int64'), 'universal_lora': Value('bool'), 'emotional_breakdown': Value('bool')}), 'steps': Value('int64')}, 'RBLOWFACE': {'version': Value('int64'), 'name': Value('string'), 'cuts': List({'lora': Value('string'), 'prompt_name': Value('string'), 'duration': Value('int64'), 'trim_frames': Value('int64'), 'universal_lora': Value('bool'), 'emotional_breakdown': Value('bool')}), 'steps': Value('int64')}, 'TEST': {'version': Value('int64'), 'name': Value('string'), 'cuts': List({'lora': Value('string'), 'duration': Value('int64'), 'trim_frames': Value('int64'), 'prompt_name': Value('string'), 'universal_lora': Value('bool'), 'emotional_breakdown': Value('bool')}), 'resolution': Value('int64'), 'steps': Value('int64')}, 'RBLOWMOUTH': {'version': Value('int64'), 'name': Value('string'), 'cuts': List({'lora': Value('string'), 'prompt_name': Value('string'), 'duration': Value('int64'), 'trim_frames': Value('int64'), 'universal_lora': Value('bool'), 'emotional_breakdown': Value('bool')}), 'steps': Value('int64')}, 'RBLOWFOREHEAD': {'version': Value('int64'), 'name': Value('string'), 'cuts': List({'lora': Value('string'), 'prompt_name': Value('string'), 'duration': Value('int64'), 'trim_frames': Value('int64'), 'universal_lora': Value('bool'), 'emotional_breakdown': Value('bool')}), 'steps': Value('int64')}}
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
BLOWJOB: struct<id: string, model: string, name: string, label: string, lora: struct<high: struct<lora_name: (... 207 chars omitted)
child 0, id: string
child 1, model: string
child 2, name: string
child 3, label: string
child 4, lora: struct<high: struct<lora_name: string, tams_lora_name: string, strength_model: int64>, low: struct<l (... 65 chars omitted)
child 0, high: struct<lora_name: string, tams_lora_name: string, strength_model: int64>
child 0, lora_name: string
child 1, tams_lora_name: string
child 2, strength_model: int64
child 1, low: struct<lora_name: string, tams_lora_name: string, strength_model: int64>
child 0, lora_name: string
child 1, tams_lora_name: string
child 2, strength_model: int64
child 5, prompts: struct<Kneeling: struct<prompt: string, description: string>>
child 0, Kneeling: struct<prompt: string, description: string>
child 0, prompt: string
child 1, description: string
LYING_BJ: struct<id: string, model: string, name: string, label: string, lora: struct<high: struct<lora_name: (... 209 chars omitted)
child 0, id: string
child 1, model: string
child 2, name: string
child 3, label: string
child 4, lora: struct<high: struct<lora_name: string, tams_lora_name: string, strength_model: int64>, low: struct<l (... 65 chars omitted)
child 0, high: struct<lora_name: string, tams_lora_name: string, strength_model: int64>
ch
...
ild 5, emotional_breakdown: bool
child 3, steps: int64
BLOW: struct<version: int64, name: string, cuts: list<item: struct<lora: string, duration: int64, trim_fra (... 97 chars omitted)
child 0, version: int64
child 1, name: string
child 2, cuts: list<item: struct<lora: string, duration: int64, trim_frames: int64, prompt_name: string, universal_ (... 39 chars omitted)
child 0, item: struct<lora: string, duration: int64, trim_frames: int64, prompt_name: string, universal_lora: bool, (... 27 chars omitted)
child 0, lora: string
child 1, duration: int64
child 2, trim_frames: int64
child 3, prompt_name: string
child 4, universal_lora: bool
child 5, emotional_breakdown: bool
child 3, steps: int64
RBLOWMOUTH: struct<version: int64, name: string, cuts: list<item: struct<lora: string, prompt_name: string, dura (... 97 chars omitted)
child 0, version: int64
child 1, name: string
child 2, cuts: list<item: struct<lora: string, prompt_name: string, duration: int64, trim_frames: int64, universal_ (... 39 chars omitted)
child 0, item: struct<lora: string, prompt_name: string, duration: int64, trim_frames: int64, universal_lora: bool, (... 27 chars omitted)
child 0, lora: string
child 1, prompt_name: string
child 2, duration: int64
child 3, trim_frames: int64
child 4, universal_lora: bool
child 5, emotional_breakdown: bool
child 3, steps: int64
to
{'BLOW': {'version': Value('int64'), 'name': Value('string'), 'cuts': List({'lora': Value('string'), 'duration': Value('int64'), 'trim_frames': Value('int64'), 'prompt_name': Value('string'), 'universal_lora': Value('bool'), 'emotional_breakdown': Value('bool')}), 'steps': Value('int64')}, 'RBLOW': {'version': Value('int64'), 'name': Value('string'), 'cuts': List({'lora': Value('string'), 'prompt_name': Value('string'), 'duration': Value('int64'), 'trim_frames': Value('int64'), 'universal_lora': Value('bool'), 'emotional_breakdown': Value('bool')}), 'steps': Value('int64')}, 'RBLOWFACE': {'version': Value('int64'), 'name': Value('string'), 'cuts': List({'lora': Value('string'), 'prompt_name': Value('string'), 'duration': Value('int64'), 'trim_frames': Value('int64'), 'universal_lora': Value('bool'), 'emotional_breakdown': Value('bool')}), 'steps': Value('int64')}, 'TEST': {'version': Value('int64'), 'name': Value('string'), 'cuts': List({'lora': Value('string'), 'duration': Value('int64'), 'trim_frames': Value('int64'), 'prompt_name': Value('string'), 'universal_lora': Value('bool'), 'emotional_breakdown': Value('bool')}), 'resolution': Value('int64'), 'steps': Value('int64')}, 'RBLOWMOUTH': {'version': Value('int64'), 'name': Value('string'), 'cuts': List({'lora': Value('string'), 'prompt_name': Value('string'), 'duration': Value('int64'), 'trim_frames': Value('int64'), 'universal_lora': Value('bool'), 'emotional_breakdown': Value('bool')}), 'steps': Value('int64')}, 'RBLOWFOREHEAD': {'version': Value('int64'), 'name': Value('string'), 'cuts': List({'lora': Value('string'), 'prompt_name': Value('string'), 'duration': Value('int64'), 'trim_frames': Value('int64'), 'universal_lora': Value('bool'), 'emotional_breakdown': Value('bool')}), 'steps': 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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