Package: Rggml 0.1.0

Rggml: Vendored 'GGML' Tensor Library with C-Callable Compute API

Vendors the CPU backend of the 'GGML' tensor library (<https://github.com/ggml-org/ggml>) as a static library and exposes its core tensor-context and matrix-multiply compute path through 'R_RegisterCCallable' C-callable entry points. This is a carrier package: it has no high-level R modeling API of its own. Other R packages link to it ('LinkingTo') to build and compute 'GGML' tensor graphs (including quantized types such as Q4_K) from their own C or C++ code without re-vendoring 'GGML'. The CPU and BLAS backends are built (dense products offload to R's own BLAS); GPU ('Vulkan') support is a possible future addition.

Authors:Sounkou Mahamane Toure [aut, cre], Georgi Gerganov [cph], The ggml.ai / llama.cpp contributors [cph], Yuri Baramykov [ctb]

Rggml_0.1.0.tar.gz

Rggml_0.1.0.tgz(r-4.6-x86_64)Rggml_0.1.0.tgz(r-4.6-arm64)Rggml_0.1.0.tgz(r-4.5-x86_64)Rggml_0.1.0.tgz(r-4.5-arm64)
Rggml_0.1.0.tar.gz(r-4.7-arm64)Rggml_0.1.0.tar.gz(r-4.7-x86_64)Rggml_0.1.0.tar.gz(r-4.6-arm64)Rggml_0.1.0.tar.gz(r-4.6-x86_64)
Rggml_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
Rggml/json (API)

# Install 'Rggml' in R:
install.packages('Rggml', repos = c('https://sounkou-bioinfo.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/sounkou-bioinfo/rfmalloc/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

altrepmallocopenblascpp

3.18 score 2 stars 1 packages 6 scripts 1 exports 0 dependencies

Last updated from:6c3512e002. Checks:12 OK, 1 WARNING. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK184
linux-devel-x86_64OK144
source / vignettesOK229
linux-release-arm64OK146
linux-release-x86_64OK136
macos-release-arm64OK99
macos-release-x86_64OK204
macos-oldrel-arm64WARNING106
macos-oldrel-x86_64OK307
windows-develOK51
windows-releaseOK54
windows-oldrelOK54
wasm-releaseOK121

Exports:ggml_version

Dependencies: