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
id: string
messages: list<item: struct<role: string, content: string>>
child 0, item: struct<role: string, content: string>
child 0, role: string
child 1, content: string
prompt: list<item: struct<role: string, content: string>>
child 0, item: struct<role: string, content: string>
child 0, role: string
child 1, content: string
completion: list<item: struct<role: string, content: string>>
child 0, item: struct<role: string, content: string>
child 0, role: string
child 1, content: string
source: string
strategy: string
candidate_index: int64
target_text: string
previous_candidates: list<item: string>
child 0, item: string
split: string
teacher_models: list<item: string>
child 0, item: string
task_ids: list<item: string>
child 0, item: string
duplicate_count: int64
teacher_count: int64
counts: struct<strict_tasks_input: int64, sequential_rows_before_dedup: int64, sequential_rows_after_dedup: (... 48 chars omitted)
child 0, strict_tasks_input: int64
child 1, sequential_rows_before_dedup: int64
child 2, sequential_rows_after_dedup: int64
child 3, duplicate_sequential_rows_removed: int64
split_rows: struct<test: int64, train: int64, validation: int64>
child 0, test: int64
child 1, train: int64
child 2, validation: int64
dedup_key: string
split_first_candidate_rows: struct<test: int64, train: int64, validation: int64>
child 0, test: int64
child 1, train: int64
child 2, validation: int64
files: struct<sequential_candidate_sft_v2.jsonl: string>
child 0, sequential_candidate_sft_v2.jsonl: string
version: string
to
{'version': Value('string'), 'source': Value('string'), 'counts': {'strict_tasks_input': Value('int64'), 'sequential_rows_before_dedup': Value('int64'), 'sequential_rows_after_dedup': Value('int64'), 'duplicate_sequential_rows_removed': Value('int64')}, 'files': {'sequential_candidate_sft_v2.jsonl': Value('string')}, 'split_rows': {'test': Value('int64'), 'train': Value('int64'), 'validation': Value('int64')}, 'split_first_candidate_rows': {'test': Value('int64'), 'train': Value('int64'), 'validation': Value('int64')}, 'dedup_key': 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
id: string
messages: list<item: struct<role: string, content: string>>
child 0, item: struct<role: string, content: string>
child 0, role: string
child 1, content: string
prompt: list<item: struct<role: string, content: string>>
child 0, item: struct<role: string, content: string>
child 0, role: string
child 1, content: string
completion: list<item: struct<role: string, content: string>>
child 0, item: struct<role: string, content: string>
child 0, role: string
child 1, content: string
source: string
strategy: string
candidate_index: int64
target_text: string
previous_candidates: list<item: string>
child 0, item: string
split: string
teacher_models: list<item: string>
child 0, item: string
task_ids: list<item: string>
child 0, item: string
duplicate_count: int64
teacher_count: int64
counts: struct<strict_tasks_input: int64, sequential_rows_before_dedup: int64, sequential_rows_after_dedup: (... 48 chars omitted)
child 0, strict_tasks_input: int64
child 1, sequential_rows_before_dedup: int64
child 2, sequential_rows_after_dedup: int64
child 3, duplicate_sequential_rows_removed: int64
split_rows: struct<test: int64, train: int64, validation: int64>
child 0, test: int64
child 1, train: int64
child 2, validation: int64
dedup_key: string
split_first_candidate_rows: struct<test: int64, train: int64, validation: int64>
child 0, test: int64
child 1, train: int64
child 2, validation: int64
files: struct<sequential_candidate_sft_v2.jsonl: string>
child 0, sequential_candidate_sft_v2.jsonl: string
version: string
to
{'version': Value('string'), 'source': Value('string'), 'counts': {'strict_tasks_input': Value('int64'), 'sequential_rows_before_dedup': Value('int64'), 'sequential_rows_after_dedup': Value('int64'), 'duplicate_sequential_rows_removed': Value('int64')}, 'files': {'sequential_candidate_sft_v2.jsonl': Value('string')}, 'split_rows': {'test': Value('int64'), 'train': Value('int64'), 'validation': Value('int64')}, 'split_first_candidate_rows': {'test': Value('int64'), 'train': Value('int64'), 'validation': Value('int64')}, 'dedup_key': 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.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Sequential respelling SFT v2 format-aware
Each row trains one candidate at a time for the spoken_ascii TTS lane. The prompt includes the source grapheme, precise IPA, format family, strategy, candidate position, and candidates already selected for that strategy. At inference, generate five rows sequentially and append each accepted candidate to the next prompt.
Rows before deduplication: 473,740. Rows after deduplication: 472,802.
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