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
metrics: struct<startup/bootstrap/gpu_allocated_gb: double, startup/bootstrap/gpu_max_allocated_gb: double, s (... 3252 chars omitted)
child 0, startup/bootstrap/gpu_allocated_gb: double
child 1, startup/bootstrap/gpu_max_allocated_gb: double
child 2, startup/bootstrap/gpu_max_reserved_gb: double
child 3, startup/bootstrap/gpu_reserved_gb: double
child 4, startup/bootstrap_sec: double
child 5, startup/build_data/gpu_allocated_gb: double
child 6, startup/build_data/gpu_max_allocated_gb: double
child 7, startup/build_data/gpu_max_reserved_gb: double
child 8, startup/build_data/gpu_reserved_gb: double
child 9, startup/build_data_sec: double
child 10, startup/build_model/gpu_allocated_gb: double
child 11, startup/build_model/gpu_max_allocated_gb: double
child 12, startup/build_model/gpu_max_reserved_gb: double
child 13, startup/build_model/gpu_reserved_gb: double
child 14, startup/build_model_sec: double
child 15, startup/build_optimizer/gpu_allocated_gb: double
child 16, startup/build_optimizer/gpu_max_allocated_gb: double
child 17, startup/build_optimizer/gpu_max_reserved_gb: double
child 18, startup/build_optimizer/gpu_reserved_gb: double
child 19, startup/build_optimizer_sec: double
child 20, startup/build_pp_schedule/gpu_allocated_gb: double
child 21, startup/build_pp_schedule/gpu_max_allocated_gb: double
child 22, startup/build_pp_schedule/gpu_max_reserved_gb: double
child 23, startup/build_pp_schedule/gpu_reserved_gb: double
...
fix_ids: list<item: int64>
child 0, item: int64
child 2, counts: struct<micro_batches: int64, real_micro_batches: int64, segments_seen: int64, skipped_padding_segmen (... 57 chars omitted)
child 0, micro_batches: int64
child 1, real_micro_batches: int64
child 2, segments_seen: int64
child 3, skipped_padding_segments: int64
child 4, train_steps: int64
child 5, validated_segments: int64
child 3, enabled: bool
child 4, manifest_sha256: string
child 5, mode: string
child 6, n_skip: int64
child 7, n_tune: int64
child 8, padding_semantics: struct<attention_mask_inactive: int64, ignore_index: int64, pad_token_id: int64>
child 0, attention_mask_inactive: int64
child 1, ignore_index: int64
child 2, pad_token_id: int64
child 9, prefix_ids_sha256: string
child 10, schema: string
child 11, segment_layout: string
repo_commit: null
wandb_name: string
wandb_project: string
artifact: string
config_sha256: string
global_step: int64
training_metrics: struct<final_loss: double, final_grad_norm: double, final_lr: double, global_step: int64, total_trai (... 88 chars omitted)
child 0, final_loss: double
child 1, final_grad_norm: double
child 2, final_lr: double
child 3, global_step: int64
child 4, total_train_steps: int64
child 5, loss_history: list<item: double>
child 0, item: double
child 6, grad_norm_history: list<item: double>
child 0, item: double
rows_sha256: string
prefix_sha256: string
to
{'artifact': Value('string'), 'config_sha256': Value('string'), 'rows_sha256': Value('string'), 'prefix_sha256': Value('string'), 'global_step': Value('int64'), 'training_metrics': {'final_loss': Value('float64'), 'final_grad_norm': Value('float64'), 'final_lr': Value('float64'), 'global_step': Value('int64'), 'total_train_steps': Value('int64'), 'loss_history': List(Value('float64')), 'grad_norm_history': List(Value('float64'))}}
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
metrics: struct<startup/bootstrap/gpu_allocated_gb: double, startup/bootstrap/gpu_max_allocated_gb: double, s (... 3252 chars omitted)
child 0, startup/bootstrap/gpu_allocated_gb: double
child 1, startup/bootstrap/gpu_max_allocated_gb: double
child 2, startup/bootstrap/gpu_max_reserved_gb: double
child 3, startup/bootstrap/gpu_reserved_gb: double
child 4, startup/bootstrap_sec: double
child 5, startup/build_data/gpu_allocated_gb: double
child 6, startup/build_data/gpu_max_allocated_gb: double
child 7, startup/build_data/gpu_max_reserved_gb: double
child 8, startup/build_data/gpu_reserved_gb: double
child 9, startup/build_data_sec: double
child 10, startup/build_model/gpu_allocated_gb: double
child 11, startup/build_model/gpu_max_allocated_gb: double
child 12, startup/build_model/gpu_max_reserved_gb: double
child 13, startup/build_model/gpu_reserved_gb: double
child 14, startup/build_model_sec: double
child 15, startup/build_optimizer/gpu_allocated_gb: double
child 16, startup/build_optimizer/gpu_max_allocated_gb: double
child 17, startup/build_optimizer/gpu_max_reserved_gb: double
child 18, startup/build_optimizer/gpu_reserved_gb: double
child 19, startup/build_optimizer_sec: double
child 20, startup/build_pp_schedule/gpu_allocated_gb: double
child 21, startup/build_pp_schedule/gpu_max_allocated_gb: double
child 22, startup/build_pp_schedule/gpu_max_reserved_gb: double
child 23, startup/build_pp_schedule/gpu_reserved_gb: double
...
fix_ids: list<item: int64>
child 0, item: int64
child 2, counts: struct<micro_batches: int64, real_micro_batches: int64, segments_seen: int64, skipped_padding_segmen (... 57 chars omitted)
child 0, micro_batches: int64
child 1, real_micro_batches: int64
child 2, segments_seen: int64
child 3, skipped_padding_segments: int64
child 4, train_steps: int64
child 5, validated_segments: int64
child 3, enabled: bool
child 4, manifest_sha256: string
child 5, mode: string
child 6, n_skip: int64
child 7, n_tune: int64
child 8, padding_semantics: struct<attention_mask_inactive: int64, ignore_index: int64, pad_token_id: int64>
child 0, attention_mask_inactive: int64
child 1, ignore_index: int64
child 2, pad_token_id: int64
child 9, prefix_ids_sha256: string
child 10, schema: string
child 11, segment_layout: string
repo_commit: null
wandb_name: string
wandb_project: string
artifact: string
config_sha256: string
global_step: int64
training_metrics: struct<final_loss: double, final_grad_norm: double, final_lr: double, global_step: int64, total_trai (... 88 chars omitted)
child 0, final_loss: double
child 1, final_grad_norm: double
child 2, final_lr: double
child 3, global_step: int64
child 4, total_train_steps: int64
child 5, loss_history: list<item: double>
child 0, item: double
child 6, grad_norm_history: list<item: double>
child 0, item: double
rows_sha256: string
prefix_sha256: string
to
{'artifact': Value('string'), 'config_sha256': Value('string'), 'rows_sha256': Value('string'), 'prefix_sha256': Value('string'), 'global_step': Value('int64'), 'training_metrics': {'final_loss': Value('float64'), 'final_grad_norm': Value('float64'), 'final_lr': Value('float64'), 'global_step': Value('int64'), 'total_train_steps': Value('int64'), 'loss_history': List(Value('float64')), 'grad_norm_history': List(Value('float64'))}}
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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