Building blocks for the atomistic machine learning models based on PyTorch and NumPy
Project description
This package contains building blocks for the atomistic machine learning models based on PyTorch and NumPy.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
metatensor_learn-0.5.0rc2.tar.gz
(25.3 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file metatensor_learn-0.5.0rc2.tar.gz.
File metadata
- Download URL: metatensor_learn-0.5.0rc2.tar.gz
- Upload date:
- Size: 25.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
98e7c4e9a3f945dbee022284271472a5e65f4643c06151dfbbf2f028f71dacd5
|
|
| MD5 |
370677d00ca924ecb1a4e9d6f8507f98
|
|
| BLAKE2b-256 |
112e1870082e01d4872c54fdf4009dd1b47cd7e480698fc790e833f428082561
|
File details
Details for the file metatensor_learn-0.5.0rc2-py3-none-any.whl.
File metadata
- Download URL: metatensor_learn-0.5.0rc2-py3-none-any.whl
- Upload date:
- Size: 32.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
79be2c07678fd3765bdcfdd0aafcaaa4420f4513d539be782a07394d041b7eac
|
|
| MD5 |
fbf821feb21f7a86d5d9978c6252e09f
|
|
| BLAKE2b-256 |
d3149e7cf9ee197468018f2aebce4e5e7b7a9ea0118de559d9ffb69315c8b94e
|
