This is the Linux app named FairChem whose latest release can be downloaded as fairchem-core-2.9.0sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named FairChem with OnWorks for free.
Suivez ces instructions pour exécuter cette application :
- 1. Téléchargé cette application sur votre PC.
- 2. Entrez dans notre gestionnaire de fichiers https://www.onworks.net/myfiles.php?username=XXXXX avec le nom d'utilisateur que vous voulez.
- 3. Téléchargez cette application dans ce gestionnaire de fichiers.
- 4. Démarrez l'émulateur en ligne OnWorks Linux ou Windows en ligne ou l'émulateur en ligne MACOS à partir de ce site Web.
- 5. Depuis le système d'exploitation OnWorks Linux que vous venez de démarrer, accédez à notre gestionnaire de fichiers https://www.onworks.net/myfiles.php?username=XXXXX avec le nom d'utilisateur que vous souhaitez.
- 6. Téléchargez l'application, installez-la et exécutez-la.
CAPTURES D'ÉCRAN
Ad
FairChem
DESCRIPTION
FAIRChem is a unified library for machine learning in chemistry and materials, consolidating data, pretrained models, demos, and application code into a single, versioned toolkit. Version 2 modernizes the stack with a cleaner core package and breaking changes relative to V1, focusing on simpler installs and a stable API surface for production and research. The centerpiece models (e.g., UMA variants) plug directly into the ASE ecosystem via a FAIRChem calculator, so users can run relaxations, molecular dynamics, spin-state energetics, and surface catalysis workflows with the same pretrained network by switching a task flag. Tasks span heterogeneous domains—catalysis (OC20-style), inorganic materials (OMat), molecules (OMol), MOFs (ODAC), and molecular crystals (OMC)—allowing one model family to serve many simulations. The README provides quick paths for pulling models (e.g., via Hugging Face access), then running energy/force predictions on GPU or CPU.
Comment ça marche
- Single library spanning materials science and quantum chemistry tasks
- Pretrained UMA models with an ASE-compatible FAIRChemCalculator
- Simple task switch (oc20, omat, omol, odac, omc) for domain-specific predictions
- V2 core with streamlined installation and reduced third-party dependencies
- Examples for relaxations, MD, and spin-gap calculations on CPU or GPU
- Actively released package with docs, demos, and model registry integration
Langage de programmation
Python
Catégories
This is an application that can also be fetched from https://sourceforge.net/projects/fairchem.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
