Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
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/webdataset/webdataset.py", line 80, in _split_generators
raise ValueError(
...<2 lines>...
)
ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
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 68, 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.
AI4Sci atomistic-materials v2
Prepared data for the atomistic-materials task of
T0-RSI/ai4sci-tasks: develop one universal crystal
potential that stays MP-compatible and accurate far from equilibrium.
pool/: training pool in ASE-LMDB shards, one directory per source: MPtrj, sAlex, MatPES-PBE, and a 35 % shard sample of the OMat24 training subsets. Every composition and parent ID of an evaluation material is removed.pool/manifest.jsonlists every file.archives/val.tar,archives/test-inputs.tar,archives/test-references.tar: validation and test splits of eight suites:- WBM discovery, MDR phonons, MP elasticity;
- PhononDB κ, MOFSimBench bulk moduli, AM26 amorphous energies and forces;
- cleavage energies, LiTraj nebDFT2k barriers.
archives/models.tar: UMA-S-1.1 and two fine-tuned baselines (FAIR Chemistry License and Acceptable Use Policy).archives/baselines.tar: the original task's 500k MPtrj + sAlex fine-tuning sample, v2-filtered.release-manifest.json: size and SHA-256 of every artifact.
Install with environment/data/materialize.sh release DIR from the task repository.
Licenses of the components:
- MPtrj: MIT;
- sAlex, OMat24 and the cleavage benchmark: CC BY 4.0;
- MatPES: BSD-3-Clause;
- Matbench Discovery references: MIT / CC BY 4.0;
- MOFSimBench and LiTraj: MIT;
- AM26: as published by Fragapane and Deringer (no license file at the pinned commit);
- UMA weights and derivatives: FAIR Chemistry License.
Cite the original datasets when using them.
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