Running Local LLMs with 'llama.cpp' Backend

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Documentation for package ‘localLLM’ version 1.1.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

localLLM-package	R Interface to llama.cpp with Runtime Library Loading
ag_news_sample	AG News classification sample
annotation_sink_csv	Create a CSV sink for streaming annotation chunks
apply_chat_template	Apply Chat Template to Format Conversations
apply_gemma_chat_template	Apply Gemma-Compatible Chat Template
backend_free	Free localLLM backend
backend_init	Initialize localLLM backend
compute_confusion_matrices	Compute confusion matrices from multi-model annotations
context_create	Create Inference Context for Text Generation
detokenize	Convert Token IDs Back to Text
document_end	Finish automatic run documentation
document_start	Start automatic run documentation
download_model	Download a model manually
explore	Compare multiple LLMs over a shared set of prompts
generate	Generate Text Using Language Model Context
generate_parallel	Generate Text in Parallel for Multiple Prompts
get_lib_path	Get Backend Library Path
get_model_cache_dir	Get the model cache directory
hardware_profile	Inspect detected hardware resources
install_localLLM	Install localLLM Backend Library
intercoder_reliability	Intercoder reliability for LLM annotations
lib_is_installed	Check if Backend Library is Installed
list_cached_models	List cached models on disk
list_ollama_models	List GGUF models managed by Ollama
localLLM	R Interface to llama.cpp with Runtime Library Loading
model_load	Load Language Model with Automatic Download Support
quick_llama	Quick LLaMA Inference
quick_llama_reset	Reset quick_llama state
set_hf_token	Configure Hugging Face access token
smart_chat_template	Smart Chat Template Application
tokenize	Convert Text to Token IDs
tokenize_test	Test tokenize function (debugging)
validate	Validate model predictions against gold labels and peer agreement