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Description

Build a Mini llama.cpp in Pure C: LLM Inference Engine from is a course on how to build a lightweight large language model (LLM) inference engine in C language published by Udemy Online Academy. Designed for software engineers, AI developers, systems programmers, and computer science enthusiasts, this course explains the fundamentals of efficient LLM inference without relying on high-level machine learning frameworks. Students will learn how to perform inference transform models, implement tensor operations, load model weights, tokenize input, efficiently manage memory, optimize matrix calculations, and generate text using autocorrelation decoding.

You will master low-level LLM inference by coding the core components of llama.cpp in standard C. You will implement model loading, acceleration, quantization, and an efficient chatbot. This is the most practical entry-level LLM engineering course for developers who want to move beyond the black boxes of AI frameworks and master real-world inference engine programming. By the end of this course, you will not only understand every key LLM inference algorithm at the code level.

What you will learn in Build a Mini llama.cpp in Pure C: LLM Inference Engine from:

  • Build a complete Mini llama.cpp inference engine from scratch in pure C
  • Understand and parse the GGUF model format used by all local LLMs
  • Master zero-copy mmap model loading for fast LLM startup
  • Implement RMSNorm, SwiGLU, and RoPE rotational positional encoding
  • Multi-head causal self-aware encoding for LLM inference
  • Learn how KV Cache works and why it speeds up production by 10-100x
  • Implement INT4 quantization and dequantization for model compression
  • Build custom tensor and matrix multiplication systems from scratch
  • Write autoregressive token generation logic and greedy sampling
  • Develop a fully interactive LLM terminal chat demo
  • Acquire real low-level C system programming skills for AI deployment
  • And…

Course specifications

Publisher: Udemy
Instructors: James Jiang
Language: English
Level: Introductory
Number of Lessons: 11
Duration: 2 hours and 36 minutes

Course topics

Build a Mini llama.cpp in Pure C: LLM Inference Engine from Prerequisites

Basic C programming knowledge (structs, pointers, file IO, functions)
Basic understanding of Makefile compilation
Fundamental knowledge of Transformer / LLM concepts
A Mac, Linux, or Windows (WSL2) computer
No prior llama.cpp or inference engine experience required

Pictures

Build a Mini llama.cpp in Pure C: LLM Inference Engine from

Build a Mini llama.cpp in Pure C: LLM Inference Engine from introduction video

Installation guide

After Extract, watch with your favorite Player.

Subtitle: None

Quality: 1080p

Downloadly link

Download Part 1 – 1 GB

Download Part 2 – 51 MB

Rapidgator link

Download Part 1 – 1 GB

Download Part 2 – 51 MB

File password (s): www.downloadly.ir

Size

1 GB

 

 

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