% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ggml.R
\docType{package}
\name{ggmlR-package}
\alias{ggmlR}
\alias{ggmlR-package}
\title{ggmlR: 'GGML' Tensor Operations for Machine Learning}
\description{
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 \url{https://github.com/ggml-org/ggml} for more information about the underlying library.
}
\seealso{
Useful links:
\itemize{
  \item \url{https://github.com/Zabis13/ggmlR}
  \item Report bugs at \url{https://github.com/Zabis13/ggmlR/issues}
}

}
\author{
\strong{Maintainer}: Yuri Baramykov \email{lbsbmsu@mail.ru}

Other contributors:
\itemize{
  \item Georgi Gerganov (Author of the GGML library) [contributor, copyright holder]
  \item Jeffrey Quesnelle (Contributor to ops.cpp) [contributor, copyright holder]
  \item Bowen Peng (Contributor to ops.cpp) [contributor, copyright holder]
  \item Mozilla Foundation (Author of llamafile/sgemm.cpp) [contributor, copyright holder]
}

}
\keyword{internal}
