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
files: struct<claims.json: string, figures/fig1.csv: string, figures/fig4c.csv: string, figures/fig5.csv: s (... 267 chars omitted)
child 0, claims.json: string
child 1, figures/fig1.csv: string
child 2, figures/fig4c.csv: string
child 3, figures/fig5.csv: string
child 4, figures/fig6.csv: string
child 5, figures/fig7.csv: string
child 6, pooled_r1.json: string
child 7, results_page.html: string
child 8, results_page.md: string
child 9, tables/table1.html: string
child 10, tables/table1.md: string
child 11, tables/table1.tex: string
child 12, tsv/pt_r1_s2.tsv: string
child 13, tsv/pt_r1_s3.tsv: string
schema: string
cells: list<item: struct<backbone: string, box: string, cell: string, checkpoint: struct<id: string, pub_di (... 780 chars omitted)
child 0, item: struct<backbone: string, box: string, cell: string, checkpoint: struct<id: string, pub_digest: struc (... 768 chars omitted)
child 0, backbone: string
child 1, box: string
child 2, cell: string
child 3, checkpoint: struct<id: string, pub_digest: struct<bytes: int64, n_files: int64, sha256: string>, ref: string>
child 0, id: string
child 1, pub_digest: struct<bytes: int64, n_files: int64, sha256: string>
child 0, bytes: int64
child 1, n_files: int64
child 2, sha256: string
child 2, ref: string
child 4, eval_command: string
child 5, eval_fingerprint: string
child 6, lineage: struc
...
child 0, item: string
child 8, training_seed: int64
child 3, norm_stats_sha256: string
child 4, step: string
child 5, train_config: string
child 6, train_overrides: list<item: string>
child 0, item: string
child 7, results: struct<path: string, sha256: string>
child 0, path: string
child 1, sha256: string
child 8, rollouts: struct<path: string, sha256: string, size: int64>
child 0, path: string
child 1, sha256: string
child 2, size: int64
child 9, run: string
child 10, serve: struct<beta: double, fields: struct<quality: string>, uncond_fields: null>
child 0, beta: double
child 1, fields: struct<quality: string>
child 0, quality: string
child 2, uncond_fields: null
child 11, served: string
child 12, training_seed: struct<ft: int64, pretrain: int64>
child 0, ft: int64
child 1, pretrain: int64
child 13, manifest: struct<path: string, sha256: string>
child 0, path: string
child 1, sha256: string
bench: struct<n_seeds: int64, name: string, r1_declaration_sha256: string, task_ids: list<item: int64>, uni (... 18 chars omitted)
child 0, n_seeds: int64
child 1, name: string
child 2, r1_declaration_sha256: string
child 3, task_ids: list<item: int64>
child 0, item: int64
child 4, units_sha256: string
release: string
to
{'bench': {'n_seeds': Value('int64'), 'name': Value('string'), 'r1_declaration_sha256': Value('string'), 'task_ids': List(Value('int64')), 'units_sha256': Value('string')}, 'cells': List({'backbone': Value('string'), 'box': Value('string'), 'cell': Value('string'), 'checkpoint': {'id': Value('string'), 'pub_digest': {'bytes': Value('int64'), 'n_files': Value('int64'), 'sha256': Value('string')}, 'ref': Value('string')}, 'eval_command': Value('string'), 'eval_fingerprint': Value('string'), 'lineage': {'arm': Value('string'), 'base': Value('string'), 'init': {'base': Value('string'), 'id': Value('string'), 'norm_stats_sha256': Value('string'), 'pub_digest': Value('string'), 'ref': Value('string'), 'step': Value('string'), 'train_config': Value('string'), 'train_overrides': List(Value('string')), 'training_seed': Value('int64')}, 'norm_stats_sha256': Value('string'), 'step': Value('string'), 'train_config': Value('string'), 'train_overrides': List(Value('string'))}, 'results': {'path': Value('string'), 'sha256': Value('string')}, 'rollouts': {'path': Value('string'), 'sha256': Value('string'), 'size': Value('int64')}, 'run': Value('string'), 'serve': {'beta': Value('float64'), 'fields': {'quality': Value('string')}, 'uncond_fields': Value('null')}, 'served': Value('string'), 'training_seed': {'ft': Value('int64'), 'pretrain': Value('int64')}, 'manifest': {'path': Value('string'), 'sha256': Value('string')}}), 'release': Value('string'), 'schema': Value('string')}
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
files: struct<claims.json: string, figures/fig1.csv: string, figures/fig4c.csv: string, figures/fig5.csv: s (... 267 chars omitted)
child 0, claims.json: string
child 1, figures/fig1.csv: string
child 2, figures/fig4c.csv: string
child 3, figures/fig5.csv: string
child 4, figures/fig6.csv: string
child 5, figures/fig7.csv: string
child 6, pooled_r1.json: string
child 7, results_page.html: string
child 8, results_page.md: string
child 9, tables/table1.html: string
child 10, tables/table1.md: string
child 11, tables/table1.tex: string
child 12, tsv/pt_r1_s2.tsv: string
child 13, tsv/pt_r1_s3.tsv: string
schema: string
cells: list<item: struct<backbone: string, box: string, cell: string, checkpoint: struct<id: string, pub_di (... 780 chars omitted)
child 0, item: struct<backbone: string, box: string, cell: string, checkpoint: struct<id: string, pub_digest: struc (... 768 chars omitted)
child 0, backbone: string
child 1, box: string
child 2, cell: string
child 3, checkpoint: struct<id: string, pub_digest: struct<bytes: int64, n_files: int64, sha256: string>, ref: string>
child 0, id: string
child 1, pub_digest: struct<bytes: int64, n_files: int64, sha256: string>
child 0, bytes: int64
child 1, n_files: int64
child 2, sha256: string
child 2, ref: string
child 4, eval_command: string
child 5, eval_fingerprint: string
child 6, lineage: struc
...
child 0, item: string
child 8, training_seed: int64
child 3, norm_stats_sha256: string
child 4, step: string
child 5, train_config: string
child 6, train_overrides: list<item: string>
child 0, item: string
child 7, results: struct<path: string, sha256: string>
child 0, path: string
child 1, sha256: string
child 8, rollouts: struct<path: string, sha256: string, size: int64>
child 0, path: string
child 1, sha256: string
child 2, size: int64
child 9, run: string
child 10, serve: struct<beta: double, fields: struct<quality: string>, uncond_fields: null>
child 0, beta: double
child 1, fields: struct<quality: string>
child 0, quality: string
child 2, uncond_fields: null
child 11, served: string
child 12, training_seed: struct<ft: int64, pretrain: int64>
child 0, ft: int64
child 1, pretrain: int64
child 13, manifest: struct<path: string, sha256: string>
child 0, path: string
child 1, sha256: string
bench: struct<n_seeds: int64, name: string, r1_declaration_sha256: string, task_ids: list<item: int64>, uni (... 18 chars omitted)
child 0, n_seeds: int64
child 1, name: string
child 2, r1_declaration_sha256: string
child 3, task_ids: list<item: int64>
child 0, item: int64
child 4, units_sha256: string
release: string
to
{'bench': {'n_seeds': Value('int64'), 'name': Value('string'), 'r1_declaration_sha256': Value('string'), 'task_ids': List(Value('int64')), 'units_sha256': Value('string')}, 'cells': List({'backbone': Value('string'), 'box': Value('string'), 'cell': Value('string'), 'checkpoint': {'id': Value('string'), 'pub_digest': {'bytes': Value('int64'), 'n_files': Value('int64'), 'sha256': Value('string')}, 'ref': Value('string')}, 'eval_command': Value('string'), 'eval_fingerprint': Value('string'), 'lineage': {'arm': Value('string'), 'base': Value('string'), 'init': {'base': Value('string'), 'id': Value('string'), 'norm_stats_sha256': Value('string'), 'pub_digest': Value('string'), 'ref': Value('string'), 'step': Value('string'), 'train_config': Value('string'), 'train_overrides': List(Value('string')), 'training_seed': Value('int64')}, 'norm_stats_sha256': Value('string'), 'step': Value('string'), 'train_config': Value('string'), 'train_overrides': List(Value('string'))}, 'results': {'path': Value('string'), 'sha256': Value('string')}, 'rollouts': {'path': Value('string'), 'sha256': Value('string'), 'size': Value('int64')}, 'run': Value('string'), 'serve': {'beta': Value('float64'), 'fields': {'quality': Value('string')}, 'uncond_fields': Value('null')}, 'served': Value('string'), 'training_seed': {'ft': Value('int64'), 'pretrain': Value('int64')}, 'manifest': {'path': Value('string'), 'sha256': Value('string')}}), 'release': Value('string'), 'schema': 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.
qvla-v1-results
Per-seed rollout logs, run records and results files behind every number the paper derives from
the evaluation rollouts (the main-results table; the headline, random-vs-filtered, methods, scaling
and conditioning figures; and the success rates in its text), plus the outputs of qvla paper tables.
cells.json- the 123 cells the paper reports: run, served name, how it was served, checkpoint, eval fingerprint, and the sha256 of each file below.rollouts/<box>/<served>.tar- the rawseed_<n>.jsonfiles of one served arm, byte-exact.runs/<box>/<arm>/- the arm's summary (arm_summary.json: its tally, eval fingerprint and benchmark) and, where the run published one, its run record (run_manifest.json: its config and work units).results/<box>/<served>.json- the same outcomes in theqvla.results/v1format.expected/- every output ofqvla paper tables(the figure data, the main-results table, the in-text numbers and the results page), withMANIFEST.json.
Reproduce them (stdlib Python >= 3.11, CPU):
qvla paper tables --results hf://axisrobotics/qvla-v1-results@v1.0 --check
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