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.
| Version: |
0.8.1 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
generics, R6, methods, stats |
| Suggests: |
testthat (≥ 3.0.0), mlr3 (≥ 0.21.0), paradox, digest, parsnip, tibble, rlang, dials, lgr, knitr, rmarkdown, Matrix, Seurat, SeuratObject, RSpectra, irlba, uwot, FNN, SingleCellExperiment, SummarizedExperiment, S4Vectors, withr, hardhat, rsample, tune, workflows |
| Published: |
2026-07-13 |
| DOI: |
10.32614/CRAN.package.ggmlR |
| Author: |
Yuri Baramykov 
[aut, cre],
Georgi Gerganov [ctb, cph] (Author of the GGML library),
Jeffrey Quesnelle [ctb, cph] (Contributor to ops.cpp),
Bowen Peng [ctb, cph] (Contributor to ops.cpp),
Mozilla Foundation [ctb, cph] (Author of llamafile/sgemm.cpp) |
| Maintainer: |
Yuri Baramykov <lbsbmsu at mail.ru> |
| BugReports: |
https://github.com/Zabis13/ggmlR/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/Zabis13/ggmlR |
| NeedsCompilation: |
yes |
| SystemRequirements: |
C++17, GNU make, libvulkan-dev, glslc (optional,
for GPU on Linux), 'Vulkan' 'SDK' (optional, for GPU on
Windows) |
| Materials: |
README, NEWS |
| CRAN checks: |
ggmlR results |