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
source: string
task_type: string
category: string
answer: string
verifier: struct<type: string, expected: string>
child 0, type: string
child 1, expected: 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
metadata: struct<campaign: string, mix: string, build_id: string, model_name: string, developer: string, devel (... 452 chars omitted)
child 0, campaign: string
child 1, mix: string
child 2, build_id: string
child 3, model_name: string
child 4, developer: string
child 5, developer_th: string
child 6, source_dataset: string
child 7, source_basis: string
child 8, synthetic_original: bool
child 9, offline_deterministic: bool
child 10, no_external_source_files_read: bool
child 11, no_benchmark_prompt_gold_answer_or_sample: bool
child 12, no_model_prediction_or_eval_sample_used: bool
child 13, single_model_greedy_only: bool
child 14, no_bon: bool
child 15, no_self_consistency: bool
child 16, no_routing: bool
child 17, no_ensemble: bool
child 18, category: string
child 19, template_id: string
child 20, focus: list<item: string>
child 0, item: string
child 21, rationale_required: bool
base_config: string
n_dropped_length: int64
name: string
tag: string
base_manifest: string
inputs: list<item: string>
child 0, item: string
failures: list<item: null>
child 0, item: null
records_file: string
next_config: string
created_at: string
n_dropped_duplicates: int64
n_promoted: int64
n_failures: int64
input_lines: int64
weight: double
to
{'name': Value('string'), 'tag': Value('string'), 'created_at': Value('string'), 'inputs': List(Value('string')), 'records_file': Value('string'), 'next_config': Value('string'), 'base_manifest': Value('string'), 'base_config': Value('string'), 'weight': Value('float64'), 'input_lines': Value('int64'), 'n_promoted': Value('int64'), 'n_failures': Value('int64'), 'n_dropped_duplicates': Value('int64'), 'n_dropped_length': Value('int64'), 'failures': List(Value('null'))}
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(
^^^^^^^^^
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 478, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2815, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/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/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 310, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 130, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
id: string
source: string
task_type: string
category: string
answer: string
verifier: struct<type: string, expected: string>
child 0, type: string
child 1, expected: 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
metadata: struct<campaign: string, mix: string, build_id: string, model_name: string, developer: string, devel (... 452 chars omitted)
child 0, campaign: string
child 1, mix: string
child 2, build_id: string
child 3, model_name: string
child 4, developer: string
child 5, developer_th: string
child 6, source_dataset: string
child 7, source_basis: string
child 8, synthetic_original: bool
child 9, offline_deterministic: bool
child 10, no_external_source_files_read: bool
child 11, no_benchmark_prompt_gold_answer_or_sample: bool
child 12, no_model_prediction_or_eval_sample_used: bool
child 13, single_model_greedy_only: bool
child 14, no_bon: bool
child 15, no_self_consistency: bool
child 16, no_routing: bool
child 17, no_ensemble: bool
child 18, category: string
child 19, template_id: string
child 20, focus: list<item: string>
child 0, item: string
child 21, rationale_required: bool
base_config: string
n_dropped_length: int64
name: string
tag: string
base_manifest: string
inputs: list<item: string>
child 0, item: string
failures: list<item: null>
child 0, item: null
records_file: string
next_config: string
created_at: string
n_dropped_duplicates: int64
n_promoted: int64
n_failures: int64
input_lines: int64
weight: double
to
{'name': Value('string'), 'tag': Value('string'), 'created_at': Value('string'), 'inputs': List(Value('string')), 'records_file': Value('string'), 'next_config': Value('string'), 'base_manifest': Value('string'), 'base_config': Value('string'), 'weight': Value('float64'), 'input_lines': Value('int64'), 'n_promoted': Value('int64'), 'n_failures': Value('int64'), 'n_dropped_duplicates': Value('int64'), 'n_dropped_length': Value('int64'), 'failures': List(Value('null'))}
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.
Kanitakorn Clean Thai Skill-Repair Seed 20260615
This is a staged synthetic dataset source for the kanitakorn Thai LLM
campaign. It contains 240 offline deterministic Thai MCQ skill-repair records.
Status: staged only. It is not a trained model checkpoint and should not be used as evidence of benchmark achievement.
Safeguards:
- Original synthetic records only.
- No benchmark prompts, gold answers, model predictions, or held-out samples were read by the builder.
- Answer labels are balanced:
a=b=c=d=e=48. - Local inspection and MCQ audit passed with zero issues.
- Contamination scan reported
0issues over9735loaded benchmark texts. - Provenance audit passed with
ok=true.
Primary files:
records.jsonlmanifest.json
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