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Llama.cpp

As explained in Build a Large Language Model (From Scratch)

A C/C++ library for efficiently running large language models, used here as the engine behind Ollama.

llama.cpp is an open-source C/C++ library for efficient large language model inference. Ollama wraps it to run models locally, including an instruction-fine-tuned Llama 3 model used for automated response evaluation. section 7.8

Its role in the evaluation workflow is operational:

  • Runs a local LLM through Ollama rather than a remote web API. section 7.8
  • Supports inference and text generation, but not model training or fine-tuning. section 7.8
  • Provides the execution layer behind commands such as `ollama run llama3` and HTTP requests to Ollama’s local chat API. section 7.8

Local evaluation engine

A Python evaluator sends prompts to Ollama at `http://localhost:11434/api/chat`, receives generated responses, and asks the local Llama 3 model to score them from 0 to 100. llama.cpp supplies the efficient C/C++ inference implementation beneath this workflow. section 7.8

How Build a Large Language Model (From Scratch) covers it

How deep it goes
Defines its implementation language and deployment role, but stops short of explaining internal algorithms or architecture.
Examples
Uses `ollama run llama3`, a local chat API, and Python scoring code as concrete integration examples.
What it assumes
Assumes familiarity with LLM inference and requires Ollama installation and startup for the demonstrated workflow.
What you can do after
Operate Ollama to run a local Llama 3 model and generate evaluation responses.
How it connects
Connects Ollama, Llama 3, inference, fine-tuning, and automated model evaluation.

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Related concepts

This explainer was generated by Manning's knowledge graph from the text of Build a Large Language Model (From Scratch). The section links point to the parts of the book it draws on.