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
config: struct<seed: int64, n_agents: int64, n_waves: int64, events_per_wave: int64, model: string, backend: (... 48 chars omitted)
child 0, seed: int64
child 1, n_agents: int64
child 2, n_waves: int64
child 3, events_per_wave: int64
child 4, model: string
child 5, backend: string
child 6, top_k: int64
child 7, forgetting_alpha: double
methods: struct<direct: struct<kl: double, wg_gap: double, entropy_gap: double, transition_js: double, distri (... 30805 chars omitted)
child 0, direct: struct<kl: double, wg_gap: double, entropy_gap: double, transition_js: double, distribution: struct< (... 3318 chars omitted)
child 0, kl: double
child 1, wg_gap: double
child 2, entropy_gap: double
child 3, transition_js: double
child 4, distribution: struct<kl: double, entropy_gap: double, num_cells: int64, cells: struct<w1:CIVIC: struct<kl: double, (... 3020 chars omitted)
child 0, kl: double
child 1, entropy_gap: double
child 2, num_cells: int64
child 3, cells: struct<w1:CIVIC: struct<kl: double, entropy_gap: double, js: double>, w1:FINSTR: struct<kl: double, (... 2954 chars omitted)
child 0, w1:CIVIC: struct<kl: double, entropy_gap: double, js: double>
child 0, kl: double
child 1, entropy_gap: double
child 2, js: double
child 1, w1:FINSTR: struct<kl: double, entropy_gap: double, js: double>
child 0, kl:
...
: double
examples: list<item: struct<method: string, agent_id: string, wave: int64, variable: string, question: string, (... 88 chars omitted)
child 0, item: struct<method: string, agent_id: string, wave: int64, variable: string, question: string, human: str (... 76 chars omitted)
child 0, method: string
child 1, agent_id: string
child 2, wave: int64
child 3, variable: string
child 4, question: string
child 5, human: string
child 6, model: string
child 7, retrieved_event_ids: list<item: string>
child 0, item: string
child 8, prompt: string
lora: struct<rank: int64, alpha: int64, dropout: double, target_modules: list<item: string>, learning_rate (... 272 chars omitted)
child 0, rank: int64
child 1, alpha: int64
child 2, dropout: double
child 3, target_modules: list<item: string>
child 0, item: string
child 4, learning_rate: double
child 5, epochs_per_event: int64
child 6, batch_size: int64
child 7, max_train_seq_len: int64
child 8, generate_batch_size: int64
child 9, max_generate_seq_len: int64
child 10, replay_size: int64
child 11, replay_weight: double
child 12, stability_weight: double
child 13, max_grad_norm: double
child 14, model_name: string
child 15, disable_thinking: bool
backbone: string
device: string
hardware: string
root: string
torch: string
max_train_seq_len: int64
status: string
train_batch_size: int64
n_agents: int64
cuda: string
n_waves: int64
model: string
to
{'status': Value('string'), 'cuda': Value('string'), 'root': Value('string'), 'torch': Value('string'), 'hardware': Value('string'), 'model': Value('string'), 'n_agents': Value('int64'), 'n_waves': Value('int64'), 'train_batch_size': Value('int64'), 'max_train_seq_len': 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
config: struct<seed: int64, n_agents: int64, n_waves: int64, events_per_wave: int64, model: string, backend: (... 48 chars omitted)
child 0, seed: int64
child 1, n_agents: int64
child 2, n_waves: int64
child 3, events_per_wave: int64
child 4, model: string
child 5, backend: string
child 6, top_k: int64
child 7, forgetting_alpha: double
methods: struct<direct: struct<kl: double, wg_gap: double, entropy_gap: double, transition_js: double, distri (... 30805 chars omitted)
child 0, direct: struct<kl: double, wg_gap: double, entropy_gap: double, transition_js: double, distribution: struct< (... 3318 chars omitted)
child 0, kl: double
child 1, wg_gap: double
child 2, entropy_gap: double
child 3, transition_js: double
child 4, distribution: struct<kl: double, entropy_gap: double, num_cells: int64, cells: struct<w1:CIVIC: struct<kl: double, (... 3020 chars omitted)
child 0, kl: double
child 1, entropy_gap: double
child 2, num_cells: int64
child 3, cells: struct<w1:CIVIC: struct<kl: double, entropy_gap: double, js: double>, w1:FINSTR: struct<kl: double, (... 2954 chars omitted)
child 0, w1:CIVIC: struct<kl: double, entropy_gap: double, js: double>
child 0, kl: double
child 1, entropy_gap: double
child 2, js: double
child 1, w1:FINSTR: struct<kl: double, entropy_gap: double, js: double>
child 0, kl:
...
: double
examples: list<item: struct<method: string, agent_id: string, wave: int64, variable: string, question: string, (... 88 chars omitted)
child 0, item: struct<method: string, agent_id: string, wave: int64, variable: string, question: string, human: str (... 76 chars omitted)
child 0, method: string
child 1, agent_id: string
child 2, wave: int64
child 3, variable: string
child 4, question: string
child 5, human: string
child 6, model: string
child 7, retrieved_event_ids: list<item: string>
child 0, item: string
child 8, prompt: string
lora: struct<rank: int64, alpha: int64, dropout: double, target_modules: list<item: string>, learning_rate (... 272 chars omitted)
child 0, rank: int64
child 1, alpha: int64
child 2, dropout: double
child 3, target_modules: list<item: string>
child 0, item: string
child 4, learning_rate: double
child 5, epochs_per_event: int64
child 6, batch_size: int64
child 7, max_train_seq_len: int64
child 8, generate_batch_size: int64
child 9, max_generate_seq_len: int64
child 10, replay_size: int64
child 11, replay_weight: double
child 12, stability_weight: double
child 13, max_grad_norm: double
child 14, model_name: string
child 15, disable_thinking: bool
backbone: string
device: string
hardware: string
root: string
torch: string
max_train_seq_len: int64
status: string
train_batch_size: int64
n_agents: int64
cuda: string
n_waves: int64
model: string
to
{'status': Value('string'), 'cuda': Value('string'), 'root': Value('string'), 'torch': Value('string'), 'hardware': Value('string'), 'model': Value('string'), 'n_agents': Value('int64'), 'n_waves': Value('int64'), 'train_batch_size': Value('int64'), 'max_train_seq_len': 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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