JARVIS-Leaderboard:
This project provides benchmark-performances of various methods for materials science applications using the datasets available in JARVIS-Tools databases. Some of the methods are: Artificial Intelligence (AI), Electronic Structure (ES), Force-field (FF), Qunatum Computation (QC) and Experiments (EXP). There are a variety of properties included in the benchmark. In addition to prediction results, we attempt to capture the underlyig software, hardware and instrumental frameworks to enhance reproducibility. This project is a part of the NIST-JARVIS infrastructure.
1 maintainer
Metadata
1 maintainer
Release files for jarvis-leaderboard 2024.10.30
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| jarvis_leaderboard-2024.10.30.tar.gz | 72.0 MB | Without provenance | Details for jarvis_leaderboard-2024.10.30.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| jarvis_leaderboard-2024.10.30-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details for jarvis_leaderboard-2024.10.30-py2.py3-none-any.whl |
Total release size: 144.1 MB
Release files / jarvis_leaderboard-2024.10.30.tar.gz
| Download URL | jarvis_leaderboard-2024.10.30.tar.gz |
|---|---|
| Size | 72.0 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
394a8864a2148d0bfff9a1a5d76d269c3505f3e3c80a2642eb71bfa2d066880d
|
|
BLAKE2b-256 checksum How to use checksums |
92e2c83220f7e476f0859e5f243411acb6c15a824288e6a0ffa925e1602ef9bc
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.10.14
|
Release files / jarvis_leaderboard-2024.10.30-py2.py3-none-any.whl
| Download URL | jarvis_leaderboard-2024.10.30-py2.py3-none-any.whl |
|---|---|
| Size | 72.1 MB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
62cd3012987e83880583801a5ed46c0b999781505f246d91554cde6fd62d81ff
|
|
BLAKE2b-256 checksum How to use checksums |
09f9a3ef58359233fd953b52f7d7bd163950bc14e5f178d984e14e21e6023cdc
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.10.14
|
Security for jarvis-leaderboard 2024.10.30
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
