Local Large Language Model Inference Engine

Enables R users to run large language models locally using 'GGUF' model files and the 'llama.cpp' inference engine. Provides a complete R interface for loading models, generating text completions, extracting vector representations, and streaming responses in real-time. Includes grammar-constrained generation for structured output, text classification, and retrieval-augmented generation (RAG) pipelines. Supports local inference without requiring cloud APIs or internet connectivity, ensuring complete data privacy and control. Based on the 'llama.cpp' project by Georgi Gerganov (2023) < https://github.com/ggml-org/llama.cpp>.


Reference manual

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install.packages("edgemodelr")

0.4.5 by Pawan Rama Mali, 8 days ago


https://github.com/PawanRamaMali/edgemodelr


Report a bug at https://github.com/PawanRamaMali/edgemodelr/issues


Browse source code at https://github.com/cran/edgemodelr


Authors: Pawan Rama Mali [aut, cre, cph] , Georgi Gerganov [aut, cph] (Author of llama.cpp and GGML library) , The ggml authors [cph] (llama.cpp and GGML contributors) , Jeffrey Quesnelle [ctb, cph] (YaRN RoPE implementation) , Bowen Peng [ctb, cph] (YaRN RoPE implementation) , pi6am [ctb] (DRY sampler from Koboldcpp) , Ivan Yurchenko [ctb] (Z-algorithm implementation) , Dirk Eddelbuettel [ctb, rev]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports Rcpp, utils, tools

Suggests testthat, knitr, rmarkdown, curl, shiny, openssl, jsonlite, httr, plumber

Linking to Rcpp

System requirements: GNU make or equivalent for building


See at CRAN