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
efc: struct<score: list<item: double>>
child 0, score: list<item: double>
child 0, item: double
axial: struct<score: list<item: double>>
child 0, score: list<item: double>
child 0, item: double
sets: struct<nemotron-3-super-120b: struct<model: string, rows: int64, layers: list<item: int64>, probes: (... 184 chars omitted)
child 0, nemotron-3-super-120b: struct<model: string, rows: int64, layers: list<item: int64>, probes: struct<efc: string, axial: str (... 5 chars omitted)
child 0, model: string
child 1, rows: int64
child 2, layers: list<item: int64>
child 0, item: int64
child 3, probes: struct<efc: string, axial: string>
child 0, efc: string
child 1, axial: string
child 1, qwen3.5-9b: struct<model: string, rows: int64, layers: list<item: int64>, probes: struct<linear: string, mlp: st (... 34 chars omitted)
child 0, model: string
child 1, rows: int64
child 2, layers: list<item: int64>
child 0, item: int64
child 3, probes: struct<linear: string, mlp: string, efc: string, axial: string>
child 0, linear: string
child 1, mlp: string
child 2, efc: string
child 3, axial: string
format: int64
to
{'format': Value('int64'), 'sets': {'nemotron-3-super-120b': {'model': Value('string'), 'rows': Value('int64'), 'layers': List(Value('int64')), 'probes': {'efc': Value('string'), 'axial': Value('string')}}, 'qwen3.5-9b': {'model': Value('string'), 'rows': Value('int64'), 'layers': List(Value('int64')), 'probes': {'linear': Value('string'), 'mlp': Value('string'), 'efc': Value('string'), 'axial': Value('string')}}}}
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 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 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
efc: struct<score: list<item: double>>
child 0, score: list<item: double>
child 0, item: double
axial: struct<score: list<item: double>>
child 0, score: list<item: double>
child 0, item: double
sets: struct<nemotron-3-super-120b: struct<model: string, rows: int64, layers: list<item: int64>, probes: (... 184 chars omitted)
child 0, nemotron-3-super-120b: struct<model: string, rows: int64, layers: list<item: int64>, probes: struct<efc: string, axial: str (... 5 chars omitted)
child 0, model: string
child 1, rows: int64
child 2, layers: list<item: int64>
child 0, item: int64
child 3, probes: struct<efc: string, axial: string>
child 0, efc: string
child 1, axial: string
child 1, qwen3.5-9b: struct<model: string, rows: int64, layers: list<item: int64>, probes: struct<linear: string, mlp: st (... 34 chars omitted)
child 0, model: string
child 1, rows: int64
child 2, layers: list<item: int64>
child 0, item: int64
child 3, probes: struct<linear: string, mlp: string, efc: string, axial: string>
child 0, linear: string
child 1, mlp: string
child 2, efc: string
child 3, axial: string
format: int64
to
{'format': Value('int64'), 'sets': {'nemotron-3-super-120b': {'model': Value('string'), 'rows': Value('int64'), 'layers': List(Value('int64')), 'probes': {'efc': Value('string'), 'axial': Value('string')}}, 'qwen3.5-9b': {'model': Value('string'), 'rows': Value('int64'), 'layers': List(Value('int64')), 'probes': {'linear': Value('string'), 'mlp': Value('string'), 'efc': Value('string'), 'axial': 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.
probe-inference parity fixture
Test fixture for the probe-inference package's parity tests (tests/test_parity.py). The tests
download this dataset at a pinned revision and check that the package reproduces reference scores on
real activations.
For each model it holds a few rows of residual-stream activations and token masks, and the reference
score of each probe on each row. It holds no probes: the tests load them from
AlignmentResearch/probe-inference-weights
at the package's pinned revision, exactly as users do.
| Directory | Model | Rows | Probes |
|---|---|---|---|
nemotron-3-super-120b/ |
nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16 |
80 | EFC, axial |
qwen3.5-9b/ |
Qwen/Qwen3.5-9B |
32 | linear, MLP, EFC, axial |
Files in each model directory:
acts.pt:{layer: Tensor[rows, seq, d_model]}in bfloat16, the outputs of decoder blocklayer(Hugging Facehidden_states[layer + 1]), over each row's follow-up window.masks.pt:tokens,prompt_mask,completion_maskandfollowup_start_positionsfor the same rows.reference.json: per probe,score(EFC, axial), orL<layer>logits pluscombined(the mean of per-layer sigmoids) for linear and MLP, one value per row.
manifest.json lists the sets and, for each, the probes' paths in the weights repository (for example
qwen3.5-9b/efc). The Nemotron rows mix two follow-up lengths, so a batch has ragged read windows (27
and 24 tokens).
Licences and attribution
The test data and this card are released by FAR AI, Inc. under the MIT licence (LICENSE).
They are derived from the models below (this fixture uses Qwen/Qwen3.5-9B and
nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16). Both upstream licences let us license derived works under our own
terms provided we include their licence texts and keep their attribution notices, so both ship here
unchanged (see NOTICE):
| Model | Licence | Licence file |
|---|---|---|
| Qwen/Qwen3.5-2B, Qwen/Qwen3.5-9B, Qwen/Qwen3.6-27B, Qwen/Qwen3.5-122B-A10B, Qwen/Qwen3.5-397B-A17B | Apache-2.0 | LICENSE-QWEN-APACHE-2.0.txt |
| nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16, nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16 | NVIDIA Nemotron Open Model License (v. December 15, 2025) | LICENSE-NVIDIA-NEMOTRON-OPEN-MODEL.txt |
Licensed by NVIDIA Corporation under the NVIDIA Nemotron Model License.
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