Datasets:

abotresol
/

neutral-vectors-gemma-4-31b-it

Tasks:

Feature Extraction

Tags:

interpretability

emotion

gemma

License:

Dataset card Files Files and versions

xet

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train

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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
story_id: string
emotion: string
story_index: int64
sha1: string
n_tokens: int64
error: null
neutral: struct<0: list<item: double>, 3: list<item: double>, 6: list<item: double>, 9: list<item: double>, 1 (... 382 chars omitted)
  child 0, 0: list<item: double>
      child 0, item: double
  child 1, 3: list<item: double>
      child 0, item: double
  child 2, 6: list<item: double>
      child 0, item: double
  child 3, 9: list<item: double>
      child 0, item: double
  child 4, 12: list<item: double>
      child 0, item: double
  child 5, 15: list<item: double>
      child 0, item: double
  child 6, 18: list<item: double>
      child 0, item: double
  child 7, 21: list<item: double>
      child 0, item: double
  child 8, 24: list<item: double>
      child 0, item: double
  child 9, 27: list<item: double>
      child 0, item: double
  child 10, 30: list<item: double>
      child 0, item: double
  child 11, 33: list<item: double>
      child 0, item: double
  child 12, 36: list<item: double>
      child 0, item: double
  child 13, 39: list<item: double>
      child 0, item: double
  child 14, 42: list<item: double>
      child 0, item: double
  child 15, 45: list<item: double>
      child 0, item: double
  child 16, 48: list<item: double>
      child 0, item: double
  child 17, 51: list<item: double>
      child 0, item: double
  child 18, 54: list<item: double>
      child 0, item: double
  child 19, 57: list<item: double>
      child 0, item: double
to
{'neutral': {'0': List(Value('float64')), '3': List(Value('float64')), '6': List(Value('float64')), '9': List(Value('float64')), '12': List(Value('float64')), '15': List(Value('float64')), '18': List(Value('float64')), '21': List(Value('float64')), '24': List(Value('float64')), '27': List(Value('float64')), '30': List(Value('float64')), '33': List(Value('float64')), '36': List(Value('float64')), '39': List(Value('float64')), '42': List(Value('float64')), '45': List(Value('float64')), '48': List(Value('float64')), '51': List(Value('float64')), '54': List(Value('float64')), '57': List(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 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
              story_id: string
              emotion: string
              story_index: int64
              sha1: string
              n_tokens: int64
              error: null
              neutral: struct<0: list<item: double>, 3: list<item: double>, 6: list<item: double>, 9: list<item: double>, 1 (... 382 chars omitted)
                child 0, 0: list<item: double>
                    child 0, item: double
                child 1, 3: list<item: double>
                    child 0, item: double
                child 2, 6: list<item: double>
                    child 0, item: double
                child 3, 9: list<item: double>
                    child 0, item: double
                child 4, 12: list<item: double>
                    child 0, item: double
                child 5, 15: list<item: double>
                    child 0, item: double
                child 6, 18: list<item: double>
                    child 0, item: double
                child 7, 21: list<item: double>
                    child 0, item: double
                child 8, 24: list<item: double>
                    child 0, item: double
                child 9, 27: list<item: double>
                    child 0, item: double
                child 10, 30: list<item: double>
                    child 0, item: double
                child 11, 33: list<item: double>
                    child 0, item: double
                child 12, 36: list<item: double>
                    child 0, item: double
                child 13, 39: list<item: double>
                    child 0, item: double
                child 14, 42: list<item: double>
                    child 0, item: double
                child 15, 45: list<item: double>
                    child 0, item: double
                child 16, 48: list<item: double>
                    child 0, item: double
                child 17, 51: list<item: double>
                    child 0, item: double
                child 18, 54: list<item: double>
                    child 0, item: double
                child 19, 57: list<item: double>
                    child 0, item: double
              to
              {'neutral': {'0': List(Value('float64')), '3': List(Value('float64')), '6': List(Value('float64')), '9': List(Value('float64')), '12': List(Value('float64')), '15': List(Value('float64')), '18': List(Value('float64')), '21': List(Value('float64')), '24': List(Value('float64')), '27': List(Value('float64')), '30': List(Value('float64')), '33': List(Value('float64')), '36': List(Value('float64')), '39': List(Value('float64')), '42': List(Value('float64')), '45': List(Value('float64')), '48': List(Value('float64')), '51': List(Value('float64')), '54': List(Value('float64')), '57': List(Value('float64'))}}
              because column names don't match

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Neutral-transcript vectors — gemma-4-31b-it (confound-projection inputs, E7)

Data provenance (what made these activations)

Probed model: google/gemma-4-31b-it (instruct)
Input corpus: abotresol/neutral-transcripts-gemma-4-31b-it — emotionally neutral everyday transcripts written by the probed model; these vectors feed the neutral-PC projection (they are NOT emotion vectors)

Per-story pooled residual-stream activations and per-emotion mean vectors, extracted with gemma4-emotion-vectors scripts/extract_emotion_vectors.py (reference-faithful adaptation of sinievanderben/emotion_experiment extract_emotion_vectors.py).

Corpus: results/neutral_transcripts_it/dialogues_grouped.jsonl (split train)
Layers: [0, 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, 36, 39, 42, 45, 48, 51, 54, 57]
Pooling: mean over non-pad tokens after position 50, truncation at 512, batch size 4, bf16 model, fp32 activations.
shards/<emotion>__<idx>.npy: one [layers, d_model] fp32 array per story.
manifest.jsonl: per-story metadata (emotion, index, text sha1, token count).
<emotion>/layer_<N>_resid.npy and emotion_vectors.json: token-weighted per-emotion means, the reference's output format.
run_config.json: full extraction config, seed 20260720, commit 8bf83d2.

Reproduce: uv run python scripts/extract_emotion_vectors.py

Per-story story set (added 2026-07-22)

shards/{story_id}.npy — one [n_layers, d_model] fp32 mean per story; manifest.jsonl — one row per story with its post-mask token count and content hash. The published per-emotion means are the token-weighted recombination of these; any alternative pooling (equal-weight, subsets, bootstrap) is reproducible from the shards in numpy alone. Provenance caveat: shards predate the padding-side fix (project TREE Q1.H3.E4) — the first-50-token skip fully applied only to the longest story per batch of 4.

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Total file size:

57.8 MB