Datasets:
The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 49, in _split_generators
import h5py
ModuleNotFoundError: No module named 'h5py'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 71, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
ANI-1x
Dataset Description
The ANI-1x dataset is a molecular-configuration dataset for training and evaluation. The data package contains training, validation, and test HDF5 shards, along with a statistics JSON file and auxiliary extxyz files. Its fields are consistent with the energy and force fields in the MACE ANI-1x configuration, making it a standard benchmark dataset for learning and validating machine-learning interatomic potentials with MACE.
The element set consists of H, C, N, and O. The original ANI-1x data comes from ANI-1x datasets (FigShare); this repository is the companion data package for OneScience MACE training and evaluation examples.
The current data package contains approximately 30 files.
Supported Tasks
This standardized data repository provides the complete data package for the ANI-1x example, including training, validation, and test sets. It can be used for:
- Training and validation of potential-energy-surface models for molecular configurations
- Potential-energy-surface fitting for molecular dynamics simulations
- Functional testing and benchmark evaluation of the MACE framework
Dataset Format and Structure
The data files are located in the data/ani1x/ directory:
| File Path | Format | shape / Content | Description |
|---|---|---|---|
ani1x/ANI1x_cc_DFT_rc5_train/train_*.h5 |
HDF5 | [N_frames, N_atoms] |
Training set, with 8 shards in total |
ani1x/ANI1x_cc_DFT_rc5_val/val_*.h5 |
HDF5 | [N_frames, N_atoms] |
Validation set, with 8 shards in total |
ani1x/ANI1x_cc_DFT_rc5_test/Default__*.h5 |
HDF5 | [N_frames, N_atoms] |
Test set, with 8 shards in total |
ani1x/ANI1x_cc_DFT_rc5_statistics.json |
JSON | Statistical information | Contains atomic_energies, avg_num_neighbors, mean, std, atomic_numbers, and r_max |
ani1x/ani1x_train.xyz |
extxyz | [N_frames, N_atoms] |
Auxiliary training-set file |
ani1x/ani1x_test.xyz |
extxyz | [N_frames, N_atoms] |
Auxiliary test-set file |
ani1x/ani1x_cc_dft.xyz |
extxyz | [N_frames, N_atoms] |
Auxiliary file for the full dataset |
metadata/sha256_manifest.txt |
SHA256 | Checksum manifest | File-integrity verification |
HDF5 Data Format
The HDF5 file structure is config_batch_*/config_*. Each configuration contains:
| Path | dtype | shape | Description |
|---|---|---|---|
atomic_numbers |
int64 |
[N_atoms] |
Atomic numbers |
positions |
float64 |
[N_atoms, 3] |
Atomic coordinates, in Å |
cell |
float64 |
[3, 3] |
Periodic cell matrix |
pbc |
bool |
[3] |
Periodic boundary conditions |
properties/energy |
float64 |
Scalar | Total configuration energy, in eV |
properties/forces |
float64 |
[N_atoms, 3] |
Atomic forces, in eV/Å |
How to Use the Dataset
Download the dataset:
hf download --dataset OneScience-Sugon/ani1x --local-dir ./data
Official OneScience Information
| Platform | OneScience Main Repository | Skills Repository |
|---|---|---|
| Gitee | https://gitee.com/onescience-ai/onescience | https://gitee.com/onescience-ai/oneskills |
| GitHub | https://github.com/onescience-ai/OneScience | https://github.com/onescience-ai/oneskills |
Limitations and License
This dataset is the example data for MACE ANI-1x; it does not contain any newly generated samples or alter the original data. The original data comes from ANI-1x datasets (FigShare), with calculations performed at the wB97X/6-31G(d) level.
- Original Source: https://springernature.figshare.com/collections/The_ANI-1ccx_and_ANI-1x_data_sets_coupled-cluster_and_density_functional_theory_properties_for_molecules/4712477
- GitHub Repository: https://github.com/aiqm/ANI1x_datasets
- License: CC0 1.0 Universal (public domain dedication)
When using the ANI-1x dataset, please cite:
- Smith, J. S.; Nebgen, B.; Lubbers, N.; Isayev, O.; Roitberg, A. E. Less Is More: Sampling Chemical Space with Active Learning. J. Chem. Phys. 2018, 148 (24), 241733. https://doi.org/10.1063/1.5023802
- Smith, J. S.; Zubatyuk, R.; Nebgen, B.; Lubbers, N.; Barros, K.; Roitberg, A. E.; Isayev, O.; Tretiak, S. The ANI-1ccx and ANI-1x Data Sets, Coupled-Cluster and Density Functional Theory Properties for Molecules. Sci. Data 2020, 7, 134. https://doi.org/10.1038/s41597-020-0473-z
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