To learn how to use KLIFF, begin with the tutorials.

Train a Stillinger-Weber potential: a good entry point to see the basics of training a physics-motivated potential.

Parameter transformation for the Stillinger-Weber potential: it is similar to Train a Stillinger-Weber potential, except that some parameters are transformed to the log space for optimization.

Train a neural network potential: walks through the steps to train a machine-learning neural network potential.

Train a neural network potential for SiC: similar to Train a neural network potential, but train for a system of multiple species.

Train a Lennard-Jones potential: similar to Train a Stillinger-Weber potential (where a KIM model is used), here the Lennard-Jones model built in KLIFF is used.

More examples can be found at https://github.com/openkim/kliff/tree/master/examples.

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