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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", "0.8.4")



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 0.8.4, https://cran.r-project.org/web/packages/ggmlR. Accessed 07 Oct. 2026.
Previous versions and publish date:
(2026-08-21 14:41), 0.5.1 (2026-02-09 20:00), 0.6.1 (2026-02-23 00:00), 0.6.3 (2026-03-18 11:30), 0.6.7 (2026-03-29 19:50), 0.7.0 (2026-04-06 07:20), 0.7.2 (2026-04-15 08:30), 0.7.5 (2026-04-20 13:10), 0.7.6 (2026-04-22 17:10), 0.7.7 (2026-05-25 17:50), 0.7.8 (2026-06-04 07:11), 0.8.1 (2026-07-14 01:40), 0.8.2 (2026-07-22 13:50)
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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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