Installation

Folax can be installed using pip. Choose the installation variant that best matches your intended use case and available hardware.

CPU Installation

The CPU-only installation is recommended for small- to medium-scale problems, rapid prototyping, and for becoming familiar with the Folax API without requiring accelerator hardware.

pip install folax[cpu]

GPU (CUDA) Installation

The CUDA-enabled installation provides GPU acceleration and is intended for high-performance workloads, large-scale simulations, and operator-learning experiments.

pip install folax[cuda]

Developer Installation

For development, experimentation with the source code, or contributing to Folax, clone the repository and install the package in editable mode. From the project root directory, run:

pip install -e .[cuda,dev]