Datasets:

issdandavis
/

scbe-system-hygiene-training-data

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
created_at_utc: timestamp[s]
hf_repo_default: string
kaggle_ref: string
outputs: list<item: string>
  child 0, item: string
privacy: string
record_count: int64
schema: string
source: string
subtitle: string
id: string
licenses: list<item: struct<name: string>>
  child 0, item: struct<name: string>
      child 0, name: string
keywords: list<item: string>
  child 0, item: string
title: string
to
{'id': Value('string'), 'keywords': List(Value('string')), 'licenses': List({'name': Value('string')}), 'subtitle': Value('string'), 'title': 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 489, 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 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, 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 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              created_at_utc: timestamp[s]
              hf_repo_default: string
              kaggle_ref: string
              outputs: list<item: string>
                child 0, item: string
              privacy: string
              record_count: int64
              schema: string
              source: string
              subtitle: string
              id: string
              licenses: list<item: struct<name: string>>
                child 0, item: struct<name: string>
                    child 0, name: string
              keywords: list<item: string>
                child 0, item: string
              title: string
              to
              {'id': Value('string'), 'keywords': List(Value('string')), 'licenses': List({'name': Value('string')}), 'subtitle': Value('string'), 'title': Value('string')}
              because column names don't match

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Status: experimental. Experiment-specific slice. Primary public dataset: scbe-aethermoore-training-data.

SCBE System Hygiene Training

Metadata-only SCBE cleanup training records generated at 2026-05-12T06:55:13Z.

This dataset teaches local-first cleanup decisions: keep harness-wired models, review ambiguous model/cache state, and turn deletion candidates into scrubbed training examples before pruning local storage.

It does not include raw cache files, model weights, local logs, database contents, credentials, or private source documents.

Files

records.jsonl: full metadata and ChatML-style messages.
records.chat.jsonl: message-only records for SFT ingestion.
records.csv: compact tabular decisions.
manifest.json: generation and count metadata.

Counts

total records: 15
keep: 6
review: 6
cleanup_candidate: 3

Downloads last month: 58

Total file size:

40.3 kB