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purvansh01
/
safetypulse-probe-bundle

Tags:
safety
red-teaming
safetypulse
lexsi-hackathon
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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
pair_id: string
category: string
harmful: string
harmless: string
source: string
annotator_2_valid: string
split: string
matched: bool
components: list<item: struct<id: string, type: string, layer: int64, index: int64, score: double, discovery_exa (... 12 chars omitted)
  child 0, item: struct<id: string, type: string, layer: int64, index: int64, score: double, discovery_exact: double>
      child 0, id: string
      child 1, type: string
      child 2, layer: int64
      child 3, index: int64
      child 4, score: double
      child 5, discovery_exact: double
direction_file: string
schema_version: string
discovery: struct<method: string, matched_pairs: bool, n_pairs: int64>
  child 0, method: string
  child 1, matched_pairs: bool
  child 2, n_pairs: int64
table_a: list<item: struct<ablation: string, refusal_rate: double, delta_vs_none: double, std: double, degene (... 14 chars omitted)
  child 0, item: struct<ablation: string, refusal_rate: double, delta_vs_none: double, std: double, degenerate: doubl (... 2 chars omitted)
      child 0, ablation: string
      child 1, refusal_rate: double
      child 2, delta_vs_none: double
      child 3, std: double
      child 4, degenerate: double
probe_set: struct<path: string, sha256: string, n_pairs: int64>
  child 0, path: string
  child 1, sha256: string
  child 2, n_pairs: int64
token_sets: struct<refuse: list<item: int64>, comply: list<item: int64>>
  child 0, refuse: list<item: int64>
      child 0, item: int64
  child 1, comply: list<item: int64>
      child 0, item: int64
base_model: struct<name: string, revision: null>
  child 0, name: string
  child 1, revision: null
reference: struct<sep_base: double, logit_gap_base: double, circ_base: double>
  child 0, sep_base: double
  child 1, logit_gap_base: double
  child 2, circ_base: double
threshold: struct<metric: string, tau_warn: double, tau_fail: double>
  child 0, metric: string
  child 1, tau_warn: double
  child 2, tau_fail: double
layer: int64
provenance: struct<git_sha: null, seed: int64, created_at: timestamp[s], torch: string, transformers: string, cu (... 137 chars omitted)
  child 0, git_sha: null
  child 1, seed: int64
  child 2, created_at: timestamp[s]
  child 3, torch: string
  child 4, transformers: string
  child 5, cuda_available: bool
  child 6, on_kaggle: bool
  child 7, smoke: bool
  child 8, peft: string
  child 9, gpus: list<item: string>
      child 0, item: string
  child 10, capability: list<item: int64>
      child 0, item: int64
  child 11, vram_gb: double
to
{'schema_version': Value('string'), 'base_model': {'name': Value('string'), 'revision': Value('null')}, 'layer': Value('int64'), 'direction_file': Value('string'), 'components': List({'id': Value('string'), 'type': Value('string'), 'layer': Value('int64'), 'index': Value('int64'), 'score': Value('float64'), 'discovery_exact': Value('float64')}), 'discovery': {'method': Value('string'), 'matched_pairs': Value('bool'), 'n_pairs': Value('int64')}, 'token_sets': {'refuse': List(Value('int64')), 'comply': List(Value('int64'))}, 'reference': {'sep_base': Value('float64'), 'logit_gap_base': Value('float64'), 'circ_base': Value('float64')}, 'threshold': {'metric': Value('string'), 'tau_warn': Value('float64'), 'tau_fail': Value('float64')}, 'probe_set': {'path': Value('string'), 'sha256': Value('string'), 'n_pairs': Value('int64')}, 'table_a': List({'ablation': Value('string'), 'refusal_rate': Value('float64'), 'delta_vs_none': Value('float64'), 'std': Value('float64'), 'degenerate': Value('float64')}), 'provenance': {'git_sha': Value('null'), 'seed': Value('int64'), 'created_at': Value('timestamp[s]'), 'torch': Value('string'), 'transformers': Value('string'), 'cuda_available': Value('bool'), 'on_kaggle': Value('bool'), 'smoke': Value('bool'), 'peft': Value('string'), 'gpus': List(Value('string')), 'capability': List(Value('int64')), 'vram_gb': Value('float64')}}
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
              pair_id: string
              category: string
              harmful: string
              harmless: string
              source: string
              annotator_2_valid: string
              split: string
              matched: bool
              components: list<item: struct<id: string, type: string, layer: int64, index: int64, score: double, discovery_exa (... 12 chars omitted)
                child 0, item: struct<id: string, type: string, layer: int64, index: int64, score: double, discovery_exact: double>
                    child 0, id: string
                    child 1, type: string
                    child 2, layer: int64
                    child 3, index: int64
                    child 4, score: double
                    child 5, discovery_exact: double
              direction_file: string
              schema_version: string
              discovery: struct<method: string, matched_pairs: bool, n_pairs: int64>
                child 0, method: string
                child 1, matched_pairs: bool
                child 2, n_pairs: int64
              table_a: list<item: struct<ablation: string, refusal_rate: double, delta_vs_none: double, std: double, degene (... 14 chars omitted)
                child 0, item: struct<ablation: string, refusal_rate: double, delta_vs_none: double, std: double, degenerate: doubl (... 2 chars omitted)
                    child 0, ablation: string
                    child 1, refusal_rate: double
                    child 2, delta_vs_none: double
                    child 3, std: double
                    child 4, degenerate: double
              probe_set: struct<path: string, sha256: string, n_pairs: int64>
                child 0, path: string
                child 1, sha256: string
                child 2, n_pairs: int64
              token_sets: struct<refuse: list<item: int64>, comply: list<item: int64>>
                child 0, refuse: list<item: int64>
                    child 0, item: int64
                child 1, comply: list<item: int64>
                    child 0, item: int64
              base_model: struct<name: string, revision: null>
                child 0, name: string
                child 1, revision: null
              reference: struct<sep_base: double, logit_gap_base: double, circ_base: double>
                child 0, sep_base: double
                child 1, logit_gap_base: double
                child 2, circ_base: double
              threshold: struct<metric: string, tau_warn: double, tau_fail: double>
                child 0, metric: string
                child 1, tau_warn: double
                child 2, tau_fail: double
              layer: int64
              provenance: struct<git_sha: null, seed: int64, created_at: timestamp[s], torch: string, transformers: string, cu (... 137 chars omitted)
                child 0, git_sha: null
                child 1, seed: int64
                child 2, created_at: timestamp[s]
                child 3, torch: string
                child 4, transformers: string
                child 5, cuda_available: bool
                child 6, on_kaggle: bool
                child 7, smoke: bool
                child 8, peft: string
                child 9, gpus: list<item: string>
                    child 0, item: string
                child 10, capability: list<item: int64>
                    child 0, item: int64
                child 11, vram_gb: double
              to
              {'schema_version': Value('string'), 'base_model': {'name': Value('string'), 'revision': Value('null')}, 'layer': Value('int64'), 'direction_file': Value('string'), 'components': List({'id': Value('string'), 'type': Value('string'), 'layer': Value('int64'), 'index': Value('int64'), 'score': Value('float64'), 'discovery_exact': Value('float64')}), 'discovery': {'method': Value('string'), 'matched_pairs': Value('bool'), 'n_pairs': Value('int64')}, 'token_sets': {'refuse': List(Value('int64')), 'comply': List(Value('int64'))}, 'reference': {'sep_base': Value('float64'), 'logit_gap_base': Value('float64'), 'circ_base': Value('float64')}, 'threshold': {'metric': Value('string'), 'tau_warn': Value('float64'), 'tau_fail': Value('float64')}, 'probe_set': {'path': Value('string'), 'sha256': Value('string'), 'n_pairs': Value('int64')}, 'table_a': List({'ablation': Value('string'), 'refusal_rate': Value('float64'), 'delta_vs_none': Value('float64'), 'std': Value('float64'), 'degenerate': Value('float64')}), 'provenance': {'git_sha': Value('null'), 'seed': Value('int64'), 'created_at': Value('timestamp[s]'), 'torch': Value('string'), 'transformers': Value('string'), 'cuda_available': Value('bool'), 'on_kaggle': Value('bool'), 'smoke': Value('bool'), 'peft': Value('string'), 'gpus': List(Value('string')), 'capability': List(Value('int64')), 'vram_gb': Value('float64')}}
              because column names don't match

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SafetyPulse probe bundle (Tiny Aya Global)

Everything safetypulse check needs to score a checkpoint of CohereLabs/tiny-aya-global: the refusal direction (resid layer 27), the 20-component refusal circuit, the 50 probe pairs and the base model's reference values (bundle f898d4c6), plus the PASS / WARN / FAIL thresholds chosen on the development runs (thresholds.json: primary variant cis_circ, τ_fail 0.818, τ_warn 0.909) and the refusal token sets. unpaired_v1/: the earlier bundle from unmatched pairs (superseded).
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