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
seed: int64
contexts_train: int64
contexts_test: int64
sequence_length: int64
action_dim: int64
latent_dim: int64
batch_size: int64
steps: int64
alignment_weight: double
adaptation_labels: list<item: int64>
child 0, item: int64
hard_failures: int64
schema_version: int64
poster_html: string
timestamp: timestamp[s]
canvas: struct<source: string, width_cm: double, height_cm: double, orientation: string, source_url: null>
child 0, source: string
child 1, width_cm: double
child 2, height_cm: double
child 3, orientation: string
child 4, source_url: null
overall: string
gates: list<item: struct<name: string, severity: string, status: string, command: list<item: string>, summa (... 210 chars omitted)
child 0, item: struct<name: string, severity: string, status: string, command: list<item: string>, summary: struct< (... 198 chars omitted)
child 0, name: string
child 1, severity: string
child 2, status: string
child 3, command: list<item: string>
child 0, item: string
child 4, summary: struct<exit_code: int64, tail: string, gate: string, status: string, rules: list<item: struct<id: in (... 73 chars omitted)
child 0, exit_code: int64
child 1, tail: string
child 2, gate: string
child 3, status: string
child 4, rules: list<item: struct<id: int64, severity: string, status: string, detail: string>>
child 0, item: struct<id: int64, severity: string, status: string, detail: string>
child 0, id: int64
child 1, severity: string
child 2, status: string
child 3, detail: string
child 5, not_run: string
child 5, artifacts: list<item: string>
child 0, item: string
skill: string
warnings: int64
to
{'schema_version': Value('int64'), 'skill': Value('string'), 'timestamp': Value('timestamp[s]'), 'poster_html': Value('string'), 'canvas': {'source': Value('string'), 'width_cm': Value('float64'), 'height_cm': Value('float64'), 'orientation': Value('string'), 'source_url': Value('null')}, 'overall': Value('string'), 'hard_failures': Value('int64'), 'warnings': Value('int64'), 'gates': List({'name': Value('string'), 'severity': Value('string'), 'status': Value('string'), 'command': List(Value('string')), 'summary': {'exit_code': Value('int64'), 'tail': Value('string'), 'gate': Value('string'), 'status': Value('string'), 'rules': List({'id': Value('int64'), 'severity': Value('string'), 'status': Value('string'), 'detail': Value('string')}), 'not_run': Value('string')}, 'artifacts': List(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 478, 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
seed: int64
contexts_train: int64
contexts_test: int64
sequence_length: int64
action_dim: int64
latent_dim: int64
batch_size: int64
steps: int64
alignment_weight: double
adaptation_labels: list<item: int64>
child 0, item: int64
hard_failures: int64
schema_version: int64
poster_html: string
timestamp: timestamp[s]
canvas: struct<source: string, width_cm: double, height_cm: double, orientation: string, source_url: null>
child 0, source: string
child 1, width_cm: double
child 2, height_cm: double
child 3, orientation: string
child 4, source_url: null
overall: string
gates: list<item: struct<name: string, severity: string, status: string, command: list<item: string>, summa (... 210 chars omitted)
child 0, item: struct<name: string, severity: string, status: string, command: list<item: string>, summary: struct< (... 198 chars omitted)
child 0, name: string
child 1, severity: string
child 2, status: string
child 3, command: list<item: string>
child 0, item: string
child 4, summary: struct<exit_code: int64, tail: string, gate: string, status: string, rules: list<item: struct<id: in (... 73 chars omitted)
child 0, exit_code: int64
child 1, tail: string
child 2, gate: string
child 3, status: string
child 4, rules: list<item: struct<id: int64, severity: string, status: string, detail: string>>
child 0, item: struct<id: int64, severity: string, status: string, detail: string>
child 0, id: int64
child 1, severity: string
child 2, status: string
child 3, detail: string
child 5, not_run: string
child 5, artifacts: list<item: string>
child 0, item: string
skill: string
warnings: int64
to
{'schema_version': Value('int64'), 'skill': Value('string'), 'timestamp': Value('timestamp[s]'), 'poster_html': Value('string'), 'canvas': {'source': Value('string'), 'width_cm': Value('float64'), 'height_cm': Value('float64'), 'orientation': Value('string'), 'source_url': Value('null')}, 'overall': Value('string'), 'hard_failures': Value('int64'), 'warnings': Value('int64'), 'gates': List({'name': Value('string'), 'severity': Value('string'), 'status': Value('string'), 'command': List(Value('string')), 'summary': {'exit_code': Value('int64'), 'tail': Value('string'), 'gate': Value('string'), 'status': Value('string'), 'rules': List({'id': Value('int64'), 'severity': Value('string'), 'status': Value('string'), 'detail': Value('string')}), 'not_run': Value('string')}, 'artifacts': List(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.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Scaled mechanism reproduction: Olaf-World / SeqΔ-REPA
This is a deliberately small, executable proxy for the mechanism in Olaf-World.
Each synthetic video has a shared 2-D action and a scene-specific nuisance
transform. The feature-difference teacher is the observable displacement.
seq_delta_repa.py compares (1) a reconstruction-only latent model against
(2) the same encoder plus a sequence-level temporal-effect alignment loss.
It evaluates zero-shot coordinate transfer to unseen scenes and few-label linear adaptation to a novel control interface. It is not a replacement for the paper's MiraData, V-JEPA2 teacher, LAM architecture, or SkyReels world model.
Run:
python seq_delta_repa.py --device cuda --steps 1800 --outdir outputs
The remote Job uses the exact command above (with 1200 steps) on an Nvidia T4.
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