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language:
- en
pretty_name: LeMaterial/Atompack
tags:
- atomistic-machine-learning
- materials-science
- chemistry
- atompack
task_categories:
- other
size_categories:
- 100M<n<1B
configs:
- config_name: default
data_files:
- split: train
path: "**"
---
# LeMaterial/Atompack
Atompack is the Hugging Face Hub repository for public atomistic ML datasets distributed in the
Atompack format.
This repository is part of the broader [LeMaterial](https://lematerial.org) effort. Its role is
distribution and serving: it exposes packaged dataset paths that can be opened directly with the
`atompack` Python package.
The data hosted here comes from upstream public datasets such as LeMat-Bulk, MatPES, MP-ALOE,
MPtrj, OMAT24, and OC20. This repository is not the original source of those datasets.
## Install
```bash
pip install atompack-db
```
Import the package as `atompack` after installation.
## Open a Dataset
```python
import atompack
db = atompack.hub.open(
repo_id="LeMaterial/Atompack",
path_in_repo="omat/train",
)
print(len(db))
print(db[0].energy)
db.close()
```
You can also download a local copy first:
```python
import atompack
local_path = atompack.hub.download(
repo_id="LeMaterial/Atompack",
path_in_repo="omat/train",
)
db = atompack.hub.open_path(local_path)
print(len(db))
db.close()
```
## Dataset Paths and Sources
The main public dataset paths currently exposed in this repository are:
- `lematbulk/pbe`, from [LeMat-Bulk](https://huggingface.co/datasets/LeMaterial/LeMat-Bulk). If you use this path, cite LeMat-Bulk.
- `matpes/pbe` and `matpes/r2scan`, from [MatPES](https://docs.materialsproject.org/collaborations/matpes). If you use these paths, cite MatPES.
- `mp_aloe`, from [MP-ALOE](https://www.nature.com/articles/s41524-025-01834-9). If you use this path, cite MP-ALOE.
- `mptrj`, from [MPtrj](https://docs.materialsproject.org/services/ml-and-ai-applications/mptrj). If you use this path, cite MPtrj.
- `oc20/s2ef_train_all`, from [Open Catalyst 2020 (OC20)](https://opencatalystproject.org/). This is the full S2EF training split exported as 10 AtomPack shards.
- `oc20/s2ef_val_id`, `oc20/s2ef_val_ood_ads`, `oc20/s2ef_val_ood_cat`, and `oc20/s2ef_val_ood_both`, from [Open Catalyst 2020 (OC20)](https://opencatalystproject.org/). These are the standard S2EF validation splits packaged as single-shard AtomPack datasets.
- `omat/train` and `omat/val`, from [OMAT24](https://huggingface.co/datasets/facebook/OMAT24). If you use these paths, cite OMAT24.
These paths may be stored as one `.atp` file or as a shard directory.
`atompack.hub.open(...)` handles both through the same read-only API.
For the OC20 exports in this repository, positions and forces are stored as `float32`, while
energies and cells are stored as `float64`.
## Why Atompack
Atompack is designed for the point where atomistic datasets stop behaving like small scientific
databases and start behaving like training corpora: repeated random reads, multiprocessing
workers, large immutable snapshots, and regular export and publish steps.
It provides:
- read-only mmap-backed access for static datasets
- direct indexed reads of full molecule records
- support for local files and shard directories
- direct open/download helpers for Hugging Face Hub paths
## More
- Project repository: <https://github.com/LeMaterial/atompack>
- LeMaterial: <https://lematerial.org>
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