The dataset viewer is not available for this subset.
Exception: HfHubHTTPError
Message: (Request ID: Root=1-6a672aa0-5a63c95b2e72e9f4674dff36;84c5f7cc-6b6a-43fd-9f2d-655efa4066e6)
429 Too Many Requests: you have reached your 'api' rate limit.
Retry after 116 seconds (0/500 requests remaining in current 300s window).
Url: https://huggingface.co/api/datasets/kairosmaterial/ELEMENTA/revision/d190a21efe82c9a78b012b351669e8804b6a163e.
We had to rate limit your IP (44.222.55.104). To continue using our service, create a HF account or login to your existing account, and make sure you pass a HF_TOKEN if you're using the API.
Traceback: 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 268, in get_dataset_config_info
builder = load_dataset_builder(
path,
...<6 lines>...
**config_kwargs,
)
File "/src/services/worker/src/worker/utils.py", line 390, in safe_load_dataset_builder
dataset_module = dataset_module_factory(
repo_dir,
revision=revision,
download_config=download_config,
)
File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1217, in dataset_module_factory
raise e1 from None
File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1192, in dataset_module_factory
).get_module()
~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 608, in get_module
standalone_yaml_path = cached_path(
hf_dataset_url(self.name, config.REPOYAML_FILENAME, revision=self.commit_hash),
download_config=download_config,
)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 180, in cached_path
).resolve_path(url_or_filename)
~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_file_system.py", line 339, in resolve_path
repo_and_revision_exist, err = self._repo_and_revision_exist(parsed.type, parsed.id, revision)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_file_system.py", line 252, in _repo_and_revision_exist
self._api.repo_info(
~~~~~~~~~~~~~~~~~~~^
repo_id, revision=revision, repo_type=repo_type, timeout=constants.HF_HUB_ETAG_TIMEOUT
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/utils/_validators.py", line 88, in _inner_fn
return fn(*args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_api.py", line 3598, in repo_info
return method(
repo_id,
...<4 lines>...
files_metadata=files_metadata,
)
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/utils/_validators.py", line 88, in _inner_fn
return fn(*args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_api.py", line 3360, in dataset_info
hf_raise_for_status(r)
~~~~~~~~~~~~~~~~~~~^^^
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/utils/_http.py", line 868, in hf_raise_for_status
raise _format(HfHubHTTPError, message, response) from e
huggingface_hub.errors.HfHubHTTPError: (Request ID: Root=1-6a672aa0-5a63c95b2e72e9f4674dff36;84c5f7cc-6b6a-43fd-9f2d-655efa4066e6)
429 Too Many Requests: you have reached your 'api' rate limit.
Retry after 116 seconds (0/500 requests remaining in current 300s window).
Url: https://huggingface.co/api/datasets/kairosmaterial/ELEMENTA/revision/d190a21efe82c9a78b012b351669e8804b6a163e.
We had to rate limit your IP (44.222.55.104). To continue using our service, create a HF account or login to your existing account, and make sure you pass a HF_TOKEN if you're using the API.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.
ELEMENTA Dataset
ELEMENTA is a large-scale, low-prior atomistic dataset labelled with density functional theory (DFT). This first public release contains:
- nearly 39 million frames from the core ELEMENTA dataset;
- the complete ELEMENTA Spin dataset, containing 4.7 million frames.
Chemical-space coverage
The core release covers:
- all unary compositions across the periodic table;
- all binary compositions;
- ternary compositions whose reduced-formula stoichiometric coefficients sum to no more than four.
The release is defined by explicit compositional and structural boundaries rather than random subsampling. It therefore preserves complete and continuous coverage within the released chemical domain, although it is a subset of the full 210-million-frame ELEMENTA corpus.
ELEMENTA Spin complements the core dataset with large-scale magnetic initializations and DFT-resolved magnetic energy landscapes.
Files
| File | Contents |
|---|---|
ELEMENTA_open.extxyz.tar.zst |
Core ELEMENTA public release |
ELEMENTA_spin.extxyz.tar.zst |
Complete ELEMENTA Spin release |
Both archives contain data in extended XYZ (extxyz) format and are compressed
with Zstandard.
To extract an archive:
tar --use-compress-program=unzstd -xf ELEMENTA_open.extxyz.tar.zst
tar --use-compress-program=unzstd -xf ELEMENTA_spin.extxyz.tar.zst
Intended uses
The datasets provide a common benchmark domain for developing and evaluating atomistic foundation models. Example applications include:
- energy and force prediction;
- out-of-composition generalization;
- polymorph recovery and ground-state identification;
- exact local-minima ranking;
- crystal structure generation;
- magnetic-state prediction;
- systematic analysis of model failures across compositions and structural environments.
Citation and License
If you use this dataset, please cite:
ELEMENTA: Toward Unbiased Scaling of Materials Data from First Principles
Please refer to the accompanying release documentation for detailed data fields, DFT protocols, quality-control procedures, licensing terms, and usage instructions.
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