{"library":"sevenn","type":"library","category":null,"description":"SevenNet is a Python library implementing Scalable EquiVariance Enabled Neural Networks, primarily for atomistic simulations and materials science. It integrates with the Atomic Simulation Environment (ASE) for molecular dynamics, energy, and force calculations. The library is actively developed, with frequent minor releases and specific checkpoint releases for new pre-trained models. The current stable version is 0.12.1.","language":"python","status":"active","version":"0.12.1","tags":["machine learning","materials science","molecular dynamics","neural network","equivariant","ase","deep learning"],"install":[{"cmd":"pip install sevenn","imports":["from sevenn.calculator import SevenNetCalculator","from sevenn.model import SevenNet","from sevenn.cli import run"]},{"cmd":"pip install sevenn[gpu]","imports":[]}],"homepage":null,"github":"https://github.com/MDIL-SNU/SevenNet","docs":null,"changelog":null,"pypi":"https://pypi.org/project/sevenn/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":35,"avg_install_s":89.3,"avg_import_s":17.25,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/sevenn/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}