ggml_save_model: Save a Full Model (Architecture + Weights)

In ggmlR: 'GGML' Tensor Operations for Machine Learning

Save a Full Model (Architecture + Weights)

Description

Saves both the architecture and trained weights of a model to an RDS file. Unlike ggml_save_weights(), which requires the model to be manually reconstructed before loading, ggml_save_model() saves everything needed to restore the model with a single call to ggml_load_model().

Usage

ggml_save_model(model, path)

Arguments

model	A trained ggml_sequential_model or ggml_functional_model.
path	File path (typically .rds).

Value

The model (invisibly).

Supported model types

• ggml_sequential_model — input shape, layer configs, trained weights, and compilation settings are all saved.

• ggml_functional_model — input/output node graphs (pure R lists, no ggml pointers) and trained node_weights are saved.

Examples

model <- ggml_model_sequential() |>
  ggml_layer_dense(16L, activation = "relu", input_shape = 4L) |>
  ggml_layer_dense(2L,  activation = "softmax")
model <- ggml_compile(model, optimizer = "adam",
                       loss = "categorical_crossentropy")
x <- matrix(runif(64 * 4), 64, 4)
y <- matrix(c(rep(c(1,0), 32), rep(c(0,1), 32)), 64, 2)
model <- ggml_fit(model, x, y, epochs = 1L, batch_size = 32L, verbose = 0L)
tmp <- tempfile(fileext = ".rds")
ggml_save_model(model, tmp)
model2 <- ggml_load_model(tmp)

ggmlR documentation built on July 14, 2026, 1:08 a.m.