% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mlr3_marshal.R
\name{ggml_marshal_model}
\alias{ggml_marshal_model}
\title{Marshal a ggmlR model to an in-memory container}
\usage{
ggml_marshal_model(model)
}
\arguments{
\item{model}{A compiled \code{ggml_sequential_model} or
\code{ggml_functional_model}.}
}
\value{
A named list with class \code{"ggmlR_marshaled"} containing the
  serialized payload and metadata. Pass it to
  \code{\link{ggml_unmarshal_model}} to reconstruct the model.
}
\description{
Serializes a trained sequential or functional ggmlR model into a
self-describing raw container suitable for transport between R sessions or
parallel workers (e.g. for \pkg{mlr3} parallel resampling and tuning).
}
\details{
The container wraps the bytes produced by \code{\link{ggml_save_model}}
together with a format tag, schema version, package/R versions, a SHA-256
integrity checksum, and a timestamp. Autograd modules are \strong{not}
supported in this version and cause the function to signal an error; the
mlr3 learners catch this and fall back to \code{marshaled = FALSE}.
}
\seealso{
\code{\link{ggml_unmarshal_model}}, \code{\link{ggml_save_model}}
}
