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
key: list<item: string>
child 0, item: string
label: int64
score: double
records_sha256: string
adaptation: string
prompt: string
object_vocabulary: string
source: string
model: string
layers: int64
feature_shape: list<item: int64>
child 0, item: int64
spatial_size: int64
method: string
complete: bool
source_records_sha256: string
prefix_definition: string
heads: int64
protocol: string
label_source: string
token_aggregation: string
feature_schema: string
feature_anchor: string
query_position: string
dtype: string
query_keys_sha256: string
source_images: int64
to
{'method': Value('string'), 'source': Value('string'), 'model': Value('string'), 'prompt': Value('string'), 'layers': Value('int64'), 'heads': Value('int64'), 'spatial_size': Value('int64'), 'feature_shape': List(Value('int64')), 'dtype': Value('string'), 'label_source': Value('string'), 'query_position': Value('string'), 'token_aggregation': Value('string'), 'prefix_definition': Value('string'), 'adaptation': Value('string'), 'feature_schema': Value('string'), 'object_vocabulary': Value('string'), 'records_sha256': Value('string'), 'protocol': Value('string'), 'source_records_sha256': Value('string'), 'query_keys_sha256': Value('string'), 'feature_anchor': Value('string'), 'source_images': Value('int64'), 'complete': Value('bool')}
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 2951, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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
key: list<item: string>
child 0, item: string
label: int64
score: double
records_sha256: string
adaptation: string
prompt: string
object_vocabulary: string
source: string
model: string
layers: int64
feature_shape: list<item: int64>
child 0, item: int64
spatial_size: int64
method: string
complete: bool
source_records_sha256: string
prefix_definition: string
heads: int64
protocol: string
label_source: string
token_aggregation: string
feature_schema: string
feature_anchor: string
query_position: string
dtype: string
query_keys_sha256: string
source_images: int64
to
{'method': Value('string'), 'source': Value('string'), 'model': Value('string'), 'prompt': Value('string'), 'layers': Value('int64'), 'heads': Value('int64'), 'spatial_size': Value('int64'), 'feature_shape': List(Value('int64')), 'dtype': Value('string'), 'label_source': Value('string'), 'query_position': Value('string'), 'token_aggregation': Value('string'), 'prefix_definition': Value('string'), 'adaptation': Value('string'), 'feature_schema': Value('string'), 'object_vocabulary': Value('string'), 'records_sha256': Value('string'), 'protocol': Value('string'), 'source_records_sha256': Value('string'), 'query_keys_sha256': Value('string'), 'feature_anchor': Value('string'), 'source_images': Value('int64'), 'complete': Value('bool')}
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.
Hallucination evaluation artifacts
Canonical COCO and AMBER detection packages are under detection/<dataset>/models/<model>/probes/<probe>/. See detection/index.json for active and pending packages. Each published package has a manifest with exact checkpoint, cache and test-result paths. Seeds are 0, 42 and 1337. TruthPrInt retains its native validation TPR-at-1%-FPR checkpoint; other detection probes use best pooled validation AUROC. Detection thresholds are validation-best F1.
COCO and AMBER are independent training/evaluation datasets. COCO 13B Ours/VIB checkpoints, caches and results are copied here; their frozen source records are not yet published, so these two packages remain pending in the index.
ablation/ contains separately indexed detection ablations; it is not part of the main detection table. evaluation/ and sweeps/ are separate training-free evaluation artifacts and are not detection checkpoints. The old COCO/AMBER detection roots were removed from the current tree after staging and verification. The pre-migration revision f815f65101c828c95f69d221b4818cf977d3a991 remains available for recovery.
- Downloads last month
- 1,897