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ggmlR  

'GGML' Tensor Operations for Machine Learning
View on CRAN: Click here


Download and install ggmlR package within the R console
Install from CRAN:
install.packages("ggmlR")

Install from Github:
library("remotes")
install_github("cran/ggmlR")

Install by package version:
library("remotes")
install_version("ggmlR", "0.5.1")



Attach the package and use:
library("ggmlR")
Maintained by
Yuri Baramykov
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-02-24
Latest Update: 2026-02-24
Description:
Provides 'R' bindings to the 'GGML' tensor library for efficient machine learning computation. Implements core tensor operations including element-wise arithmetic, reshaping, and matrix multiplication. Supports neural network layers (attention, convolutions, normalization), activation functions, and quantization. Features optimization/training API with 'AdamW' (Adam with Weight decay) and 'SGD' (Stochastic Gradient Descent) optimizers, 'MSE' (Mean Squared Error) and cross-entropy losses. Multi-backend support with CPU and optional 'Vulkan' GPU (Graphics Processing Unit) acceleration. See <https://github.com/ggml-org/ggml> for more information about the underlying library.
How to cite:
Yuri Baramykov (2026). ggmlR: 'GGML' Tensor Operations for Machine Learning. R package version 0.5.1, https://cran.r-project.org/web/packages/ggmlR. Accessed 13 Mar. 2026.
Previous versions and publish date:
0.5.1 (2026-02-09 20:00)
Other packages that cited ggmlR R package
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Complete documentation for ggmlR
Functions, R codes and Examples using the ggmlR R package
Full ggmlR package functions and examples
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