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llamaR  

Interface for Large Language Models via 'llama.cpp'
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("llamaR", "0.2.2")



Attach the package and use:
library("llamaR")
Maintained by
Yuri Baramykov
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-03-05
Latest Update: 2026-03-05
Description:
Provides 'R' bindings to 'llama.cpp' for running Large Language Models ('LLMs') locally with optional 'Vulkan' GPU acceleration via 'ggmlR'. Supports model loading, text generation, 'tokenization', token-to-piece conversion, 'embeddings' (single and batch), encoder-decoder inference, low-level batch management, chat templates, 'LoRA' adapters, explicit backend/device selection, multi-GPU split, and 'NUMA' optimization. Includes a high-level 'ragnar'-compatible embedding provider ('embed_llamar'). Built on top of 'ggmlR' for efficient tensor operations.
How to cite:
Yuri Baramykov (2026). llamaR: Interface for Large Language Models via 'llama.cpp'. R package version 0.2.2, https://cran.r-project.org/web/packages/llamaR. Accessed 12 Sep. 2026.
Previous versions and publish date:
(2026-08-27 14:00), 0.2.2 (2026-03-05 20:20), 0.2.3 (2026-04-06 12:10), 0.2.4 (2026-05-27 19:30), 0.2.5 (2026-07-02 09:10)
Other packages that cited llamaR R package
View llamaR citation profile
Other R packages that llamaR depends, imports, suggests or enhances
Complete documentation for llamaR
Functions, R codes and Examples using the llamaR R package
Full llamaR package functions and examples
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