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
doc_id: int64
doc: struct<question: string, answer: int64, A: string, B: string, C: string, D: string, Category: string (... 25 chars omitted)
child 0, question: string
child 1, answer: int64
child 2, A: string
child 3, B: string
child 4, C: string
child 5, D: string
child 6, Category: string
child 7, Human Accuracy: double
target: string
arguments: list<item: list<item: string>>
child 0, item: list<item: string>
child 0, item: string
resps: list<item: list<item: string>>
child 0, item: list<item: string>
child 0, item: string
filtered_resps: list<item: string>
child 0, item: string
filter: string
metrics: list<item: string>
child 0, item: string
doc_hash: string
prompt_hash: string
target_hash: string
exact_match: double
name: string
category: string
kind: string
model_load_seconds: double
task: string
cost: int64
num_fewshot: int64
seconds: double
group: string
to
{'name': Value('string'), 'kind': Value('string'), 'task': Value('string'), 'group': Value('string'), 'category': Value('string'), 'num_fewshot': Value('int64'), 'cost': Value('int64'), 'metrics': {'exact_match,none': Value('float64'), 'exact_match_stderr,none': Value('float64'), 'n': Value('int64')}, 'seconds': Value('float64'), 'model_load_seconds': 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 2951, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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
doc_id: int64
doc: struct<question: string, answer: int64, A: string, B: string, C: string, D: string, Category: string (... 25 chars omitted)
child 0, question: string
child 1, answer: int64
child 2, A: string
child 3, B: string
child 4, C: string
child 5, D: string
child 6, Category: string
child 7, Human Accuracy: double
target: string
arguments: list<item: list<item: string>>
child 0, item: list<item: string>
child 0, item: string
resps: list<item: list<item: string>>
child 0, item: list<item: string>
child 0, item: string
filtered_resps: list<item: string>
child 0, item: string
filter: string
metrics: list<item: string>
child 0, item: string
doc_hash: string
prompt_hash: string
target_hash: string
exact_match: double
name: string
category: string
kind: string
model_load_seconds: double
task: string
cost: int64
num_fewshot: int64
seconds: double
group: string
to
{'name': Value('string'), 'kind': Value('string'), 'task': Value('string'), 'group': Value('string'), 'category': Value('string'), 'num_fewshot': Value('int64'), 'cost': Value('int64'), 'metrics': {'exact_match,none': Value('float64'), 'exact_match_stderr,none': Value('float64'), 'n': Value('int64')}, 'seconds': Value('float64'), 'model_load_seconds': 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.
chatbot-ft 평가 기록
chatbot-ft 의 벤치마크 결과와 LLM-as-a-judge 기록. scripts/hf_store.py 가 자동으로 동기화한다.
benchmarks/<모델>/ run_benchmark.py 결과 (summary.md/json, raw/, logs/)
judge/conversations/<모델>/<생성조건 해시>/<실행ID>.jsonl 모델별 대화 (generation_config.json 의 조건이 같으면 상대 모델과 무관하게 재사용)
judge/pairs/<A>_vs_<B>/judgments_<평가자>/<실행ID>.jsonl 판정 기록 (순서를 바꿔 2회)
judge/pairs/<A>_vs_<B>/summary_<평가자>.md/json, review_<평가자>/ 집계·정성 검토 문서
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