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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
step: int64
val_bpb: double
model_config: struct<sequence_len: int64, vocab_size: int64, n_layer: int64, n_head: int64, n_kv_head: int64, n_em (... 34 chars omitted)
child 0, sequence_len: int64
child 1, vocab_size: int64
child 2, n_layer: int64
child 3, n_head: int64
child 4, n_kv_head: int64
child 5, n_embd: int64
child 6, window_pattern: string
user_config: struct<run: string, device_type: string, fp8: bool, fp8_recipe: string, depth: int64, aspect_ratio: (... 601 chars omitted)
child 0, run: string
child 1, device_type: string
child 2, fp8: bool
child 3, fp8_recipe: string
child 4, depth: int64
child 5, aspect_ratio: int64
child 6, head_dim: int64
child 7, max_seq_len: int64
child 8, window_pattern: string
child 9, num_iterations: int64
child 10, target_flops: double
child 11, target_param_data_ratio: double
child 12, device_batch_size: int64
child 13, total_batch_size: int64
child 14, embedding_lr: double
child 15, unembedding_lr: double
child 16, weight_decay: double
child 17, matrix_lr: double
child 18, scalar_lr: double
child 19, warmup_steps: int64
child 20, warmdown_ratio: double
child 21, final_lr_frac: double
child 22, resume_from_step: int64
child 23, seed: int64
child 24, dataloader: string
child 25, data_seed: int64
child 26, eval_every: int64
child 27, eval_tokens: int64
child 28, core_metric_every: int64
child 29, core_metric_max_per_task: int64
child 30, sample_every: int64
child
...
e
child 6, N_fine_arts: double
child 7, P_language_literature: double
child 8, Q_science: double
child 9, R_adjacent_QT: double
child 10, R_adjacent_other: double
child 11, R_medicine: double
child 12, S_agriculture: double
child 13, T_technology: double
child 14, other_tail: double
child 2, placed: struct<B_philosophy_religion: int64, H_social_sciences: int64, R_adjacent_other: int64, T_technology (... 247 chars omitted)
child 0, B_philosophy_religion: int64
child 1, H_social_sciences: int64
child 2, R_adjacent_other: int64
child 3, T_technology: int64
child 4, G_geography_anthro: int64
child 5, N_fine_arts: int64
child 6, R_medicine: int64
child 7, J_political_science: int64
child 8, R_adjacent_QT: int64
child 9, P_language_literature: int64
child 10, L_education: int64
child 11, K_law: int64
child 12, Q_science: int64
child 13, other_tail: int64
child 14, S_agriculture: int64
child 3, draw: int64
child 4, pool: string
child 5, pq_idx: int64
child 6, rg_idx: int64
child 7, epoch: int64
loop_state: struct<min_val_bpb: double, smooth_train_loss: double, total_training_time: double>
child 0, min_val_bpb: double
child 1, smooth_train_loss: double
child 2, total_training_time: double
git_branch: string
git_commit: string
dataset: string
git_dirty: bool
created: timestamp[s]
name: string
tokenizer: string
mixture: string
to
{'name': Value('string'), 'created': Value('timestamp[s]'), 'git_commit': Value('string'), 'git_branch': Value('string'), 'git_dirty': Value('bool'), 'dataset': Value('string'), 'mixture': Value('string'), 'tokenizer': 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
step: int64
val_bpb: double
model_config: struct<sequence_len: int64, vocab_size: int64, n_layer: int64, n_head: int64, n_kv_head: int64, n_em (... 34 chars omitted)
child 0, sequence_len: int64
child 1, vocab_size: int64
child 2, n_layer: int64
child 3, n_head: int64
child 4, n_kv_head: int64
child 5, n_embd: int64
child 6, window_pattern: string
user_config: struct<run: string, device_type: string, fp8: bool, fp8_recipe: string, depth: int64, aspect_ratio: (... 601 chars omitted)
child 0, run: string
child 1, device_type: string
child 2, fp8: bool
child 3, fp8_recipe: string
child 4, depth: int64
child 5, aspect_ratio: int64
child 6, head_dim: int64
child 7, max_seq_len: int64
child 8, window_pattern: string
child 9, num_iterations: int64
child 10, target_flops: double
child 11, target_param_data_ratio: double
child 12, device_batch_size: int64
child 13, total_batch_size: int64
child 14, embedding_lr: double
child 15, unembedding_lr: double
child 16, weight_decay: double
child 17, matrix_lr: double
child 18, scalar_lr: double
child 19, warmup_steps: int64
child 20, warmdown_ratio: double
child 21, final_lr_frac: double
child 22, resume_from_step: int64
child 23, seed: int64
child 24, dataloader: string
child 25, data_seed: int64
child 26, eval_every: int64
child 27, eval_tokens: int64
child 28, core_metric_every: int64
child 29, core_metric_max_per_task: int64
child 30, sample_every: int64
child
...
e
child 6, N_fine_arts: double
child 7, P_language_literature: double
child 8, Q_science: double
child 9, R_adjacent_QT: double
child 10, R_adjacent_other: double
child 11, R_medicine: double
child 12, S_agriculture: double
child 13, T_technology: double
child 14, other_tail: double
child 2, placed: struct<B_philosophy_religion: int64, H_social_sciences: int64, R_adjacent_other: int64, T_technology (... 247 chars omitted)
child 0, B_philosophy_religion: int64
child 1, H_social_sciences: int64
child 2, R_adjacent_other: int64
child 3, T_technology: int64
child 4, G_geography_anthro: int64
child 5, N_fine_arts: int64
child 6, R_medicine: int64
child 7, J_political_science: int64
child 8, R_adjacent_QT: int64
child 9, P_language_literature: int64
child 10, L_education: int64
child 11, K_law: int64
child 12, Q_science: int64
child 13, other_tail: int64
child 14, S_agriculture: int64
child 3, draw: int64
child 4, pool: string
child 5, pq_idx: int64
child 6, rg_idx: int64
child 7, epoch: int64
loop_state: struct<min_val_bpb: double, smooth_train_loss: double, total_training_time: double>
child 0, min_val_bpb: double
child 1, smooth_train_loss: double
child 2, total_training_time: double
git_branch: string
git_commit: string
dataset: string
git_dirty: bool
created: timestamp[s]
name: string
tokenizer: string
mixture: string
to
{'name': Value('string'), 'created': Value('timestamp[s]'), 'git_commit': Value('string'), 'git_branch': Value('string'), 'git_dirty': Value('bool'), 'dataset': Value('string'), 'mixture': Value('string'), 'tokenizer': 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.
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