metatomic is a library that defines a common interface between atomistic
machine learning models, and atomistic simulation engines. Our main goal is to
define and train models once, and then be able to re-use them across many
different simulation engines (such as LAMMPS, GROMACS, etc.). We strive to
achieve this goal without imposing any structure on the model itself, and to
allow any model architecture to be used.
Documentation
For details, tutorials, and examples, please have a look at our documentation.
Contributors
Thanks goes to all people that make metatensor possible:
We always welcome new contributors. If you want to help us take a look at our contribution guidelines and afterwards you may start with an open issue marked as good first issue.
Release files for metatomic 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| metatomic-0.1.0.tar.gz | 4.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| metatomic-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 7.8 kB
Release files / metatomic-0.1.0.tar.gz
| Download URL | metatomic-0.1.0.tar.gz |
|---|---|
| Size | 4.1 kB |
| Tags | Source |
|
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.12.8
|
Release files / metatomic-0.1.0-py3-none-any.whl
| Download URL | metatomic-0.1.0-py3-none-any.whl |
|---|---|
| Size | 3.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.12.8
|
