rinfa is an R interface to the Rust machine learning library linfa.
The linfa crate is composed of several different modules, each implementing support for a given kind of model. For module model1, the code that "bridges" R and that linfa module is in src/rust/src/model1.rs. The model1.rs module will supply a (non-exported) fit() and predict() R function for the given model type, with names fit_model_a() and predict_model_a(), where model_a is the name of the "model type" in tidymodels that corresponds to the kind of model implemented in the linfa module. (There's not always a 1-to-1 relationship between model1 and model_a.) fit_model_a() has an "XY" interface (i.e. numeric model matrix X, vector outcome Y). fit_model1() is the lowest-level R interface to model1, is not exported, and is not intended for use by end-users.
fit_model_a() is wrapped by an exported but @keywords internal function .linfa_model_a(), which also has an XY interface. .linfa_model_a() takes care of argument checking, calling the internal function, and putting together a classed R object. While this interface is exported, it should not be considered stable.
The "public" interface to rinfa models is via tidymodels (or, more specifically, parsnip). To use rinfa (and thus .linfa_model_a()) as a modeling engine, use the code model_a(engine = "rinfa"). Models can be fitted either with an XY interface (which will result in no model.matrix() overhead) or the formula interface.