New features

Production-ready inference options
- Full inference (from ionic configuration to observables) on either a single GPU or distributed across multiple CPU (multi-GPU support still in development)
- Access to (volumetric) observables within seconds
Fast training speeds due to optimal GPU usage
Training on large data sets through improved lazy-loading functionalitites and data shuffling routines
Fast hyperparameter optimization through distributed optimizers (optuna) and training-free surrogate metrics (NASWOT/ACSD)
Easy-to-use interface through single Parameters object for reproducibolity and modular design
Internal caching system for intermediate quantities (e.g. DOS, density, band energy) for improved performance
Experimental features for advanced users:
- MinterPy: Polynomial interpolation based descriptors
- OpenPMD
- OF-DFT-MD interface to create initial configurations for ML based sampling

Change notes: