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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
question: string
model_answer: string
origin: struct<source_line: int64, question_id: string, source_line_sha256: string, branch: string>
child 0, source_line: int64
child 1, question_id: string
child 2, source_line_sha256: string
child 3, branch: string
source_pool_protocol_sha256: string
status: string
script_sha256: string
files: struct<offline_requests.jsonl: struct<uncompressed_bytes: int64, uncompressed_sha256: string, record (... 290 chars omitted)
child 0, offline_requests.jsonl: struct<uncompressed_bytes: int64, uncompressed_sha256: string, records: int64, shards: list<item: st (... 66 chars omitted)
child 0, uncompressed_bytes: int64
child 1, uncompressed_sha256: string
child 2, records: int64
child 3, shards: list<item: struct<file: string, records: int64, bytes: int64, sha256: string>>
child 0, item: struct<file: string, records: int64, bytes: int64, sha256: string>
child 0, file: string
child 1, records: int64
child 2, bytes: int64
child 3, sha256: string
child 1, online_questions.jsonl: struct<uncompressed_bytes: int64, uncompressed_sha256: string, records: int64, shards: list<item: st (... 66 chars omitted)
child 0, uncompressed_bytes: int64
child 1, uncompressed_sha256: string
child 2, records: int64
child 3, shards: list<item: struct<file: string, records: int64, bytes: int64, sha256: string>>
child 0, item: struct<file: string, records: int64, bytes: int64, sha256: string>
child 0, file: string
child 1, records: int64
child 2, bytes: int64
child 3, sha256: string
to
{'status': Value('string'), 'source_pool_protocol_sha256': Value('string'), 'script_sha256': Value('string'), 'files': {'offline_requests.jsonl': {'uncompressed_bytes': Value('int64'), 'uncompressed_sha256': Value('string'), 'records': Value('int64'), 'shards': List({'file': Value('string'), 'records': Value('int64'), 'bytes': Value('int64'), 'sha256': Value('string')})}, 'online_questions.jsonl': {'uncompressed_bytes': Value('int64'), 'uncompressed_sha256': Value('string'), 'records': Value('int64'), 'shards': List({'file': Value('string'), 'records': Value('int64'), 'bytes': Value('int64'), 'sha256': Value('string')})}}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 544, 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 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 361, 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 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
question: string
model_answer: string
origin: struct<source_line: int64, question_id: string, source_line_sha256: string, branch: string>
child 0, source_line: int64
child 1, question_id: string
child 2, source_line_sha256: string
child 3, branch: string
source_pool_protocol_sha256: string
status: string
script_sha256: string
files: struct<offline_requests.jsonl: struct<uncompressed_bytes: int64, uncompressed_sha256: string, record (... 290 chars omitted)
child 0, offline_requests.jsonl: struct<uncompressed_bytes: int64, uncompressed_sha256: string, records: int64, shards: list<item: st (... 66 chars omitted)
child 0, uncompressed_bytes: int64
child 1, uncompressed_sha256: string
child 2, records: int64
child 3, shards: list<item: struct<file: string, records: int64, bytes: int64, sha256: string>>
child 0, item: struct<file: string, records: int64, bytes: int64, sha256: string>
child 0, file: string
child 1, records: int64
child 2, bytes: int64
child 3, sha256: string
child 1, online_questions.jsonl: struct<uncompressed_bytes: int64, uncompressed_sha256: string, records: int64, shards: list<item: st (... 66 chars omitted)
child 0, uncompressed_bytes: int64
child 1, uncompressed_sha256: string
child 2, records: int64
child 3, shards: list<item: struct<file: string, records: int64, bytes: int64, sha256: string>>
child 0, item: struct<file: string, records: int64, bytes: int64, sha256: string>
child 0, file: string
child 1, records: int64
child 2, bytes: int64
child 3, sha256: string
to
{'status': Value('string'), 'source_pool_protocol_sha256': Value('string'), 'script_sha256': Value('string'), 'files': {'offline_requests.jsonl': {'uncompressed_bytes': Value('int64'), 'uncompressed_sha256': Value('string'), 'records': Value('int64'), 'shards': List({'file': Value('string'), 'records': Value('int64'), 'bytes': Value('int64'), 'sha256': Value('string')})}, 'online_questions.jsonl': {'uncompressed_bytes': Value('int64'), 'uncompressed_sha256': Value('string'), 'records': Value('int64'), 'shards': List({'file': Value('string'), 'records': Value('int64'), 'bytes': Value('int64'), 'sha256': 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.
Shared math feedback candidate inputs
This archive contains 383,537 unscored generated-answer records and 184,538 online question rows covering the same 184,502 normalized question IDs. It is a candidate input corpus, not a newly judged feedback dataset or an evaluated model.
The pool intersects pre-existing offline and online question IDs and excludes exact normalized matches to five math test sets. Six overlapping questions and 129 offline-only questions were excluded; one empty generated answer was omitted. Duplicate-row weights, source order and original strings are retained. Historical positive conditions were not reused.
Each offline record contains question, model_answer and origin metadata (source line, branch and SHA256). Online records contain question and source row identity. Historical pos/neg branch names are provenance labels, not newly validated correctness judgments. Original generator and selection history remain unverified. Exact overlap exclusion does not establish semantic or pretraining decontamination.
manifest.json records every shard hash, line count and the SHA256 of each concatenated original JSONL file. Shards are in numeric order. Concatenating their gzip-decoded bytes recovers the corresponding JSONL exactly. The shared-pool protocol fingerprint is included for auditability.
No API credentials, model weights, critic judgments, training budget or performance claims are included.
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