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
schema_version: int64
archive: string
files: list<item: struct<path: string, size_bytes: int64, sha256: string>>
child 0, item: struct<path: string, size_bytes: int64, sha256: string>
child 0, path: string
child 1, size_bytes: int64
child 2, sha256: string
trajectory_count: int64
members: list<item: struct<dataset_key: string, member_key: string, stratum: string, formula: string, atom_co (... 206 chars omitted)
child 0, item: struct<dataset_key: string, member_key: string, stratum: string, formula: string, atom_count: int64, (... 194 chars omitted)
child 0, dataset_key: string
child 1, member_key: string
child 2, stratum: string
child 3, formula: string
child 4, atom_count: int64
child 5, trajectory_count: int64
child 6, frame_count: int64
child 7, split_counts: struct<train: int64, val: int64, test: int64>
child 0, train: int64
child 1, val: int64
child 2, test: int64
child 8, data_path: string
child 9, data_sha256: string
child 10, metadata_path: string
child 11, metadata_sha256: string
member_count: int64
group_count: int64
family: string
to
{'schema_version': Value('int64'), 'family': Value('string'), 'group_count': Value('int64'), 'member_count': Value('int64'), 'trajectory_count': Value('int64'), 'members': List({'dataset_key': Value('string'), 'member_key': Value('string'), 'stratum': Value('string'), 'formula': Value('string'), 'atom_count': Value('int64'), 'trajectory_count': Value('int64'), 'frame_count': Value('int64'), 'split_counts': {'train': Value('int64'), 'val': Value('int64'), 'test': Value('int64')}, 'data_path': Value('string'), 'data_sha256': Value('string'), 'metadata_path': Value('string'), 'metadata_sha256': 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
schema_version: int64
archive: string
files: list<item: struct<path: string, size_bytes: int64, sha256: string>>
child 0, item: struct<path: string, size_bytes: int64, sha256: string>
child 0, path: string
child 1, size_bytes: int64
child 2, sha256: string
trajectory_count: int64
members: list<item: struct<dataset_key: string, member_key: string, stratum: string, formula: string, atom_co (... 206 chars omitted)
child 0, item: struct<dataset_key: string, member_key: string, stratum: string, formula: string, atom_count: int64, (... 194 chars omitted)
child 0, dataset_key: string
child 1, member_key: string
child 2, stratum: string
child 3, formula: string
child 4, atom_count: int64
child 5, trajectory_count: int64
child 6, frame_count: int64
child 7, split_counts: struct<train: int64, val: int64, test: int64>
child 0, train: int64
child 1, val: int64
child 2, test: int64
child 8, data_path: string
child 9, data_sha256: string
child 10, metadata_path: string
child 11, metadata_sha256: string
member_count: int64
group_count: int64
family: string
to
{'schema_version': Value('int64'), 'family': Value('string'), 'group_count': Value('int64'), 'member_count': Value('int64'), 'trajectory_count': Value('int64'), 'members': List({'dataset_key': Value('string'), 'member_key': Value('string'), 'stratum': Value('string'), 'formula': Value('string'), 'atom_count': Value('int64'), 'trajectory_count': Value('int64'), 'frame_count': Value('int64'), 'split_counts': {'train': Value('int64'), 'val': Value('int64'), 'test': Value('int64')}, 'data_path': Value('string'), 'data_sha256': Value('string'), 'metadata_path': Value('string'), 'metadata_sha256': 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.
GenODE processed molecular coordinates
Prepared molecular-coordinate trajectories with fixed atom order per member, deterministic trajectory-level train/validation/test splits, and quality masks.
| Group | Members | Trajectories |
|---|---|---|
| molecule_3d_set1 | 6 | 597 |
| molecule_3d_set2 | 6 | 602 |
| molecule_3d_set3 | 6 | 600 |
| Total | 18 | 1,799 |
Format
genode-processed-molecule-coordinates.zip contains three group manifests and 18 pairs of molecule_3d_dataset.npz / molecule_3d_metadata.json. Each NPZ stores float32 coords with shape (frames, atoms, 3), atom symbols, frame/trajectory identifiers, trajectory boundaries, relative scientific source names, frame RMSD, and duplicate/transition/discontinuity masks. String arrays are ordinary NumPy Unicode arrays; object-pickle arrays are absent.
Metadata records atom order, molecular formula, trajectory lengths, stored split seed and split IDs, quality summaries, and the canonical member_key. Coordinate arrays and trajectory splits are unchanged. Train, validation and test trajectory sets are disjoint and cover each member. dataset-manifest.json lists every member and file checksum; package-contents.json and SHA256SUMS.txt support integrity verification.
Download and unpack
from pathlib import Path
from huggingface_hub import snapshot_download
import zipfile
import numpy as np
download = Path(snapshot_download(
"mpstoryfans/genode-molecule-coord", repo_type="dataset"
))
with zipfile.ZipFile(download / "genode-processed-molecule-coordinates.zip") as package:
package.extractall("genode-molecule-data")
# Use a data_path from dataset-manifest.json relative to genode-molecule-data.
# Load NPZ arrays with np.load(path, allow_pickle=False).
Prepared members are under genode-molecule-data/data/molecule_3d. Research users should respect the stored trajectory splits and quality masks. Matching retrained fields are available from the field checkpoint repository.
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