reexports

compile

evaluate

These objects are imported from other packages. Follow the links
below to see their documentation.
<dl>
 <dt>generics</dt>
<dd><code><a href="https://generics.r-lib.org/reference/compile.html">compile</a></code>, <code><a href="https://generics.r-lib.org/reference/evaluate.html">evaluate</a></code>, <code><a href="https://generics.r-lib.org/reference/fit.html">fit</a></code></dd>
</dl>

internal

Provides 'R' bindings to the 'GGML' tensor library for machine
learning, optimized for 'Vulkan' GPU acceleration with a transparent CPU
fallback. The package features a 'Keras'-like sequential API and a
'PyTorch'-style 'autograd' engine for building, training, and deploying
neural networks. Key capabilities include high-performance 5D tensor
operations, 'f16' precision, and efficient quantization. It supports
native 'ONNX' model import (50+ operators) and 'GGUF' weight loading
from the 'llama.cpp' and 'Hugging Face' ecosystems. Designed for
zero-overhead inference via dedicated weight buffering, it integrates
seamlessly as a 'parsnip' engine for 'tidymodels' and provides
first-class learners for the 'mlr3' framework.
See <https://github.com/ggml-org/ggml> for more information about the
underlying library.

Yuri Baramykov

ggmlR

'GGML' Tensor Operations for Machine Learning

reexports function

These objects are imported from other packages. Follow the links
below to see their documentation.
<dl>
 <dt>generics</dt>
<dd><code><a href='https://generics.r-lib.org/reference/compile.html'>compile</a></code>, <code><a href='https://generics.r-lib.org/reference/evaluate.html'>evaluate</a></code>, <code><a href='https://generics.r-lib.org/reference/fit.html'>fit</a></code></dd>


</dl>

reexports: Objects exported from other packages

Description

Arguments