ggmlR

R 패키지 메타데이터와 수집 신호를 모아 봅니다.

Packages / CRAN / ggmlR

ggmlR

v0.8.4
Repository CRANLicense MIT + file LICENSELifecycle activeNeeds compilation yes
Package pageReferenceSourceDOIREADMENEWS
DOI
10.32614/CRAN.package.ggmlR
Reverse imports
118
Reverse depends
128

Core Signals

첫 화면에서 판단해야 할 수집 신호를 먼저 배치합니다.

2
Reverse imports
118
Reverse depends
128

Supported Backends

DESCRIPTION에서 감지한 backend 관련 package입니다.

0
backend package 신호가 없습니다.

Quick Facts

기본 메타데이터를 작은 카드와 토큰으로 압축합니다.

profile
Repository
CRAN
Version
0.8.4
License
MIT + file LICENSE
Lifecycle
active
Needs compilation
yes
Reverse depends
128
Reverse imports
118
Last observed
2026-08-22
CRAN
cran.r-project.org/package=ggmlR

수집 소스별 패키지 정보

1개 소스
CRAN
0.8.4
2026-08-22
License
MIT + file LICENSE
Depends
R (>= 4.1.0)
Imports
generics, R6, methods, stats, utils
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
Needs compilation
yes
Reverse depends
128
Reverse imports
118
Lifecycle
active
Last observed
2026-08-22 01:15:43

이 패키지가 의존하는 패키지

5개 표시전체 31개
PackageTypeSpec
generics
CRAN · 0.8.4 · 2026-08-23
Importsgenerics
methods
CRAN · 0.8.4 · 2026-08-23
Importsmethods
R6
CRAN · 0.8.4 · 2026-08-23
ImportsR6
stats
CRAN · 0.8.4 · 2026-08-23
Importsstats
utils
CRAN · 0.8.4 · 2026-08-23
Importsutils
1 / 7

이 패키지를 쓰는 패키지

5개 표시전체 5개
PackageTypeSpec
llamaR
0.2.5
CRAN · 2026-08-23
DependsggmlR
sd2R
0.2.1
CRAN · 2026-08-23
ImportsggmlR (>= 0.5.0)
llamaR
0.2.5
CRAN · 2026-08-23
LinkingToggmlR
sd2R
0.2.1
CRAN · 2026-08-23
LinkingToggmlR
cayleyR
0.2.6
CRAN · 2026-08-23
SuggestsggmlR
1 / 1

Reverse dependency summary

4 types
TypePackages
Depends1
Imports1
LinkingTo2
Suggests1

패키지 페이지

Reverse depends
2
Reverse imports
3
Reverse suggests
2
All links
84
Repository
CRAN
Version
0.8.2
Collected
2026-08-20 01:16:25
Package page
https://cran.r-project.org/web/packages/ggmlR/index.html
DOI
10.32614/CRAN.package.ggmlR
CRAN checks
https://cran.r-project.org/web/checks/check_results_ggmlR.html
README
https://cran.r-project.org/web/packages/ggmlR/readme/README.html
NEWS
https://cran.r-project.org/web/packages/ggmlR/news/news.html
Reference HTML
https://cran.r-project.org/web/packages/ggmlR/refman/ggmlR.html
Reference PDF
https://cran.r-project.org/web/packages/ggmlR/ggmlR.pdf
Source package
https://cran.r-project.org/src/contrib/ggmlR_0.8.2.tar.gz
Archive
https://CRAN.R-project.org/src/contrib/Archive/ggmlR
Page fields
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)
BugReports
https://github.com/Zabis13/ggmlR/issues
CRAN Checks
ggmlR results
DOI
10.32614/CRAN.package.ggmlR
License
MIT + file LICENSE
Maintainer
Yuri Baramykov <lbsbmsu at mail.ru> [email to maintainer is undeliverable]
Materials
README , NEWS
NeedsCompilation
yes
Old Sources
ggmlR archive
Package Source
ggmlR_0.8.2.tar.gz
Published
2026-07-22
Reference Manual
ggmlR.html , ggmlR.pdf
Reverse Depends
llamaR
Reverse Imports
sd2R
Reverse Linking To
llamaR , sd2R
Reverse Suggests
cayleyR
SystemRequirements
C++17, GNU make, libvulkan-dev, glslc (optional, for GPU on Linux), 'Vulkan' 'SDK' (optional, for GPU on Windows)
URL
https://github.com/Zabis13/ggmlR
Version
0.8.2
Vignettes
03. Autograd Engine ( source , R code ) 08. Data-Parallel Training ( source , R code ) 10. Using ggmlR as a Backend in Your Package ( source , R code ) 06. GPU / Vulkan Backend ( source , R code ) 02. Keras-like API in ggmlR ( source , R code ) 05. mlr3 Integration ( source , R code ) 12. Multi-GPU Parallelism Modes ( source , R code ) 09. ONNX Model Import ( source , R code ) 07. Quantization ( source , R code ) 01. Quickstart: from data to prediction in ~10 lines ( source , R code ) 11. Single-cell GPU Acceleration with Seurat ( source , R code ) 04. tidymodels / parsnip Integration ( source , R code )
Windows Binaries
r-devel: ggmlR_0.8.2.zip , r-release: ggmlR_0.8.2.zip , r-oldrel: ggmlR_0.8.2.zip
MacOS Binaries
r-release (arm64): ggmlR_0.8.2.tgz , r-oldrel (arm64): ggmlR_0.8.2.tgz , r-release (x86_64): ggmlR_0.8.2.tgz , r-oldrel (x86_64): ggmlR_0.8.2.tgz
Version
0.8.2
Published
2026-07-22
DOI
10.32614/CRAN.package.ggmlR
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)
https://orcid.org/0009-0000-7627-4217
Maintainer
Yuri Baramykov <lbsbmsu at mail.ru> [email to maintainer is undeliverable]
BugReports
https://github.com/Zabis13/ggmlR/issues
https://github.com/Zabis13/ggmlR/issues
License
MIT + file LICENSE
MITLICENSE
URL
https://github.com/Zabis13/ggmlR
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
READMENEWS
CRAN Checks
ggmlR results
ggmlR results
Reference Manual
ggmlR.html , ggmlR.pdf
ggmlR.htmlggmlR.pdf
Vignettes
03. Autograd Engine ( source , R code ) 08. Data-Parallel Training ( source , R code ) 10. Using ggmlR as a Backend in Your Package ( source , R code ) 06. GPU / Vulkan Backend ( source , R code ) 02. Keras-like API in ggmlR ( source , R code ) 05. mlr3 Integration ( source , R code ) 12. Multi-GPU Parallelism Modes ( source , R code ) 09. ONNX Model Import ( source , R code ) 07. Quantization ( source , R code ) 01. Quickstart: from data to prediction in ~10 lines ( source , R code ) 11. Single-cell GPU Acceleration with Seurat ( source , R code ) 04. tidymodels / parsnip Integration ( source , R code )
03. Autograd EnginesourceR code08. Data-Parallel TrainingsourceR code10. Using ggmlR as a Backend in Your PackagesourceR code06. GPU / Vulkan BackendsourceR code02. Keras-like API in ggmlRsourceR code05. mlr3 IntegrationsourceR code12. Multi-GPU Parallelism Modessource
Package Source
ggmlR_0.8.2.tar.gz
ggmlR_0.8.2.tar.gz
Windows Binaries
r-devel: ggmlR_0.8.2.zip , r-release: ggmlR_0.8.2.zip , r-oldrel: ggmlR_0.8.2.zip
ggmlR_0.8.2.zipggmlR_0.8.2.zipggmlR_0.8.2.zip
MacOS Binaries
r-release (arm64): ggmlR_0.8.2.tgz , r-oldrel (arm64): ggmlR_0.8.2.tgz , r-release (x86_64): ggmlR_0.8.2.tgz , r-oldrel (x86_64): ggmlR_0.8.2.tgz
ggmlR_0.8.2.tgzggmlR_0.8.2.tgzggmlR_0.8.2.tgzggmlR_0.8.2.tgz
Old Sources
ggmlR archive
ggmlR archive
Reverse Depends
llamaR
llamaR
Reverse Imports
sd2R
sd2R
Reverse Linking To
llamaR , sd2R
llamaRsd2R
Reverse Suggests
cayleyR
cayleyR
Page sections 4
Documentation
Heading
Documentation
Links
[{"label":"ggmlR.html","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/refman/ggmlR.html"},{"label":"ggmlR.pdf","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/ggmlR.pdf"},{"label":"03. Autograd Engine","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/autograd-engine.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/autograd-engine.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/autograd-engine.R"},{"label":"08. Data-Parallel Training","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/data-parallel-training.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/data-parallel-training.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/data-parallel-training.R"},{"label":"10. Using ggmlR as a Backend in Your Package","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/embedding-ggmlR.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/embedding-ggmlR.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/embedding-ggmlR.R"},{"label":"06. GPU / Vulkan Backend","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/gpu-vulkan.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/gpu-vulkan.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/gpu-vulkan.R"},{"label":"02. Keras-like API in ggmlR","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/keras-like-api.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/keras-like-api.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/keras-like-api.R"},{"label":"05. mlr3 Integration","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/mlr3-integration.html"},{"label":"source","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/mlr3-integration.Rmd"},{"label":"R code","section":"","type":"","url":"https://cran.r-project.org/web/packages/ggmlR/vignettes/mlr3-integration.R"}]
Text
Reference manual: ggmlR.html , ggmlR.pdf Vignettes: 03. Autograd Engine ( source , R code ) 08. Data-Parallel Training ( source , R code ) 10. Using ggmlR as a Backend in Your Package ( source , R code ) 06. GPU / Vulkan Backend ( source , R code ) 02. Keras-like API in ggmlR ( source , R code ) 05. mlr3 Integration ( source , R code ) 12. Multi-GPU Parallelism Modes ( source , R code ) 09. ONNX Model Import ( source , R code ) 07. Quantization ( source , R code ) 01. Quickstart: from data to prediction in ~10 lines ( source , R code ) 11. Single-cell GPU Acceleration with Seurat ( source , R code ) 04. tidymodels / parsnip Integration ( source , R code )
Downloads
Heading
Downloads
Links
[{"label":"ggmlR_0.8.2.tar.gz","section":"","type":"","url":"https://cran.r-project.org/src/contrib/ggmlR_0.8.2.tar.gz"},{"label":"ggmlR_0.8.2.zip","section":"","type":"","url":"https://cran.r-project.org/bin/windows/contrib/4.7/ggmlR_0.8.2.zip"},{"label":"ggmlR_0.8.2.zip","section":"","type":"","url":"https://cran.r-project.org/bin/windows/contrib/4.6/ggmlR_0.8.2.zip"},{"label":"ggmlR_0.8.2.zip","section":"","type":"","url":"https://cran.r-project.org/bin/windows/contrib/4.5/ggmlR_0.8.2.zip"},{"label":"ggmlR_0.8.2.tgz","section":"","type":"","url":"https://cran.r-project.org/bin/macosx/sonoma-arm64/contrib/4.6/ggmlR_0.8.2.tgz"},{"label":"ggmlR_0.8.2.tgz","section":"","type":"","url":"https://cran.r-project.org/bin/macosx/big-sur-arm64/contrib/4.5/ggmlR_0.8.2.tgz"},{"label":"ggmlR_0.8.2.tgz","section":"","type":"","url":"https://cran.r-project.org/bin/macosx/big-sur-x86_64/contrib/4.6/ggmlR_0.8.2.tgz"},{"label":"ggmlR_0.8.2.tgz","section":"","type":"","url":"https://cran.r-project.org/bin/macosx/big-sur-x86_64/contrib/4.5/ggmlR_0.8.2.tgz"},{"label":"ggmlR archive","section":"","type":"","url":"https://CRAN.R-project.org/src/contrib/Archive/ggmlR"}]
Text
Package source: ggmlR_0.8.2.tar.gz Windows binaries: r-devel: ggmlR_0.8.2.zip , r-release: ggmlR_0.8.2.zip , r-oldrel: ggmlR_0.8.2.zip macOS binaries: r-release (arm64): ggmlR_0.8.2.tgz , r-oldrel (arm64): ggmlR_0.8.2.tgz , r-release (x86_64): ggmlR_0.8.2.tgz , r-oldrel (x86_64): ggmlR_0.8.2.tgz Old sources: ggmlR archive
Reverse dependencies
Heading
Reverse dependencies
Links
[{"label":"llamaR","section":"","type":"","url":"https://cran.r-project.org/web/packages/llamaR/index.html"},{"label":"sd2R","section":"","type":"","url":"https://cran.r-project.org/web/packages/sd2R/index.html"},{"label":"llamaR","section":"","type":"","url":"https://cran.r-project.org/web/packages/llamaR/index.html"},{"label":"sd2R","section":"","type":"","url":"https://cran.r-project.org/web/packages/sd2R/index.html"},{"label":"cayleyR","section":"","type":"","url":"https://cran.r-project.org/web/packages/cayleyR/index.html"}]
Text
Reverse depends: llamaR Reverse imports: sd2R Reverse linking to: llamaR , sd2R Reverse suggests: cayleyR
Linking
Heading
Linking
Links
[{"label":"https://CRAN.R-project.org/package=ggmlR","section":"","type":"","url":"https://CRAN.R-project.org/package=ggmlR"}]
Text
Please use the canonical form https://CRAN.R-project.org/package=ggmlR to link to this page.
Materials 2
READMENEWS
Documentation 38
ggmlR.htmlggmlR.pdf03. Autograd EnginesourceR code08. Data-Parallel TrainingsourceR code10. Using ggmlR as a Backend in Your PackagesourceR code06. GPU / Vulkan BackendsourceR code02. Keras-like API in ggmlRsourceR code05. mlr3 IntegrationsourceR code12. Multi-GPU Parallelism ModessourceR code09. ONNX Model ImportsourceR code07. QuantizationsourceR code01. Quickstart: from data to prediction in ~10 linessourceR code11. Single-cell GPU Acceleration with SeuratsourceR code04. tidymodels / parsnip IntegrationsourceR code
Vignettes 36
03. Autograd EnginesourceR code08. Data-Parallel TrainingsourceR code10. Using ggmlR as a Backend in Your PackagesourceR code06. GPU / Vulkan BackendsourceR code02. Keras-like API in ggmlRsourceR code05. mlr3 IntegrationsourceR code12. Multi-GPU Parallelism ModessourceR code09. ONNX Model ImportsourceR code07. QuantizationsourceR code01. Quickstart: from data to prediction in ~10 linessourceR code11. Single-cell GPU Acceleration with SeuratsourceR code04. tidymodels / parsnip IntegrationsourceR code
Downloads 9
ggmlR_0.8.2.tar.gzggmlR_0.8.2.zipggmlR_0.8.2.zipggmlR_0.8.2.zipggmlR_0.8.2.tgzggmlR_0.8.2.tgzggmlR_0.8.2.tgzggmlR_0.8.2.tgzggmlR archive
All page links 84
genericsR6methodsstatstestthatmlr3paradoxdigestparsniptibblerlangdialslgrknitrrmarkdownMatrixSeuratSeuratObjectRSpectrairlbauwotFNNSingleCellExperimentSummarizedExperiment10.32614/CRAN.package.ggmlRhttps://orcid.org/0009-0000-7627-4217https://github.com/Zabis13/ggmlR/issuesMITLICENSEhttps://github.com/Zabis13/ggmlRREADMENEWSggmlR resultsggmlR.htmlggmlR.pdf03. Autograd EnginesourceR code08. Data-Parallel TrainingsourceR code10. Using ggmlR as a Backend in Your PackagesourceR code06. GPU / Vulkan BackendsourceR code02. Keras-like API in ggmlRsourceR code05. mlr3 IntegrationsourceR code12. Multi-GPU Parallelism ModessourceggmlR_0.8.2.tar.gzggmlR_0.8.2.zipggmlR_0.8.2.zipggmlR_0.8.2.zipggmlR_0.8.2.tgzggmlR_0.8.2.tgzggmlR_0.8.2.tgzggmlR_0.8.2.tgzggmlR archivellamaRsd2RcayleyRR code09. ONNX Model ImportsourceR code07. QuantizationsourceR code01. Quickstart: from data to prediction in ~10 linessourceR code11. Single-cell GPU Acceleration with SeuratsourceR code04. tidymodels / parsnip IntegrationsourceR codehttps://CRAN.R-project.org/package=ggmlR

버전 이력

RepositoryVersionPublishedFirst seenLast seenDocs
CRAN0.7.62026-04-222026-05-252026-05-31
CRAN0.7.52026-04-202026-05-312026-05-31
CRAN0.7.22026-04-152026-05-312026-05-31
CRAN0.7.02026-04-062026-05-312026-05-31
CRAN0.6.72026-03-292026-05-312026-05-31
CRAN0.6.32026-03-182026-05-312026-05-31
CRAN0.6.12026-02-232026-05-312026-05-31
CRAN0.5.12026-02-092026-05-312026-05-31
CRAN0.8.42026-08-222026-08-22
CRAN0.8.22026-07-232026-07-23
CRAN0.8.12026-07-152026-07-15
CRAN0.7.82026-07-092026-07-10
CRAN0.7.72026-06-042026-06-04

보안

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