fairchem

We have hosted the application fairchem in order to run this application in our online workstations with Wine or directly.

Quick description about fairchem:

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.

Features:

• 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

Programming Language: Python.
Categories: