ocp
Use AI to model and discover new catalysts for use in renewable energy storage to help in addressing climate change.
https://github.com/open-catalyst-project/ocp
Category: Renewable Energy
Sub Category: Hydro Energy
Last synced: about 21 hours ago
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Repository metadata
FAIR Chemistry's library of machine learning methods for chemistry
- Host: GitHub
- URL: https://github.com/open-catalyst-project/ocp
- Owner: facebookresearch
- License: other
- Created: 2019-09-26T04:47:27.000Z (over 5 years ago)
- Default Branch: main
- Last Pushed: 2025-04-23T00:05:32.000Z (7 days ago)
- Last Synced: 2025-04-23T00:35:09.007Z (7 days ago)
- Language: Python
- Homepage: https://fair-chem.github.io/
- Size: 27.7 MB
- Stars: 1,044
- Watchers: 27
- Forks: 294
- Open Issues: 19
- Releases: 23
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
README.md
fairchem
is the FAIR Chemistry's centralized repository of all its data, models, demos, and application efforts for materials science and quantum chemistry.
⚠️ If you cloned the repo before January 17, 2025 and are actively developing, please read this announcement.
Documentation
If you are looking for Open-Catalyst-Project/ocp
, it can now be found at fairchem.core
. Visit its corresponding documentation here.
Contents
The repository is organized into several directories to help you find what you are looking for:
fairchem.core
: State of the art machine learning models for materials science and chemistryfairchem.data
: Dataset downloads and input generation codesfairchem.demo
: Python API for the Open Catalyst Demofairchem.applications
: Follow up applications and works (AdsorbML, CatTSunami, etc.)
Installation
Packages can be installed in your environment by the following:
pip install -e packages/fairchem-{fairchem-package-name}
fairchem.core
requires you to first create your environment
Quick Start
Pretrained models can be used directly with ASE through our OCPCalculator
interface:
from ase.build import fcc100, add_adsorbate, molecule
from ase.optimize import LBFGS
from fairchem.core import OCPCalculator
# Set up your system as an ASE atoms object
slab = fcc100("Cu", (3, 3, 3), vacuum=8)
adsorbate = molecule("CO")
add_adsorbate(slab, adsorbate, 2.0, "bridge")
calc = OCPCalculator(
model_name="EquiformerV2-31M-S2EF-OC20-All+MD",
local_cache="pretrained_models",
cpu=False,
)
slab.calc = calc
# Set up LBFGS dynamics object
dyn = LBFGS(slab)
dyn.run(0.05, 100)
If you are interested in training your own models or fine-tuning on your datasets, visit the documentation for more details and examples.
Why a single repository?
Since many of our repositories rely heavily on our other repositories, a single repository makes it really easy to test and ensure consistency across repositories. This should also help simplify the installation process for users who are interested in integrating many of the efforts into one place.
LICENSE
fairchem
is available under a MIT License.
Owner metadata
- Name: Meta Research
- Login: facebookresearch
- Email:
- Kind: organization
- Description:
- Website: https://opensource.fb.com
- Location: Menlo Park, California
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/16943930?v=4
- Repositories: 1060
- Last ynced at: 2024-12-17T01:36:52.238Z
- Profile URL: https://github.com/facebookresearch
GitHub Events
Total
- Create event: 7
- Release event: 1
- Issues event: 12
- Watch event: 8
- Delete event: 6
- Issue comment event: 22
- Push event: 5
- Pull request event: 7
- Fork event: 3
Last Year
- Create event: 7
- Release event: 1
- Issues event: 12
- Watch event: 8
- Delete event: 6
- Issue comment event: 22
- Push event: 5
- Pull request event: 7
- Fork event: 3
Dependencies
- actions/download-artifact v4 composite
- pypa/gh-action-pypi-publish release/v1 composite
- ase *
- fairchem-core *
- fairchem-data-oc *
- networkx *
- numpy >=1.25.0
- scipy *
- torch >=2.2
- actions/stale v8.0.0 composite
- actions/checkout v4 composite
- actions/upload-artifact v4 composite
- actions/checkout v4 composite
- actions/setup-python v5 composite
- actions/download-artifact v4 composite
- pypa/gh-action-pypi-publish release/v1 composite
- actions/cache v4 composite
- actions/checkout v4 composite
- actions/setup-python v5 composite
- codecov/codecov-action v4 composite
- ase *
- e3nn >=0.5
- lmdb *
- numba *
- numpy >=1.25.0
- orjson *
- pymatgen >=2023.10.3
- pyyaml *
- submitit *
- tensorboard *
- torch >=2.2
- tqdm *
- urllib3 *
- wandb *
- ase @git+https://gitlab.com/ase/ase.git@dc86a19a280741aa2b42a08d0fa63a8d0348e225
- quacc [sella]>=0.7.6
- sella ==2.3.3
- dataclasses-json == 0.6.0
- inquirer == 3.1.3
- requests == 2.31.0
- responses == 0.23.2
- tenacity == 8.2.3
- tqdm == 4.66.1
- torch_cluster ==1.6.3
- torch_geometric ==2.3.0
- torch_scatter ==2.1.2
- torch_sparse ==0.6.18
- ase ==3.22.1
- numpy ==1.23.5
- torch ==2.2.0
- actions/checkout v4 composite
- actions/setup-python v5 composite
- actions/upload-artifact v4 composite
- actions/download-artifact v4 composite
- peaceiris/actions-gh-pages v3 composite
- peaceiris/actions-gh-pages v4 composite
- actions/cache v4 composite
- actions/checkout v4 composite
- actions/setup-python v5 composite
- actions/checkout v4 composite
- release-drafter/release-drafter v6 composite
- release-drafter/release-drafter v6 composite
- release-drafter/release-drafter v6 composite
- release-drafter/release-drafter v6 composite
Score: -Infinity