llamaR: Interface for Large Language Models via 'llama.cpp'

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Authors: Yuri Baramykov
Cited by: 0

Abstract

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.

Fields of Study & Subjects

Topic Modeling Natural Language Processing Techniques Data Analysis with R

Publication details

Publication date
5 March 2026
Language
EN
Document type
Dataset