LLMForEverybody
Basic Information
LLMForEverybody is a curated, bilingual technical handbook and learning repository about large language models and their industrial use. It collects structured articles and translations that explain core concepts such as transformer architecture, pre-training, optimizers, activation functions, attention mechanisms, position encoding, tokenizers, parallel training strategies and training frameworks. It also covers deployment and inference topics including vLLM, TGI, TensorRT-LLM and Ollama, plus practical guidance on latency, throughput and private/on‚Äëpremises deployment. Later chapters discuss fine‚Äëtuning methods (PEFT, LoRA, QLoRA), quantization, GPU parallelism, prompt engineering, agent design and RAG (retrieval augmented generation) architectures. The repo includes math primers (linear algebra, calculus, probability), enterprise adoption notes and evaluation metrics. The material targets practitioners, students and engineers who want a systematic, entry‚Äëto‚Äëintermediate reference to design, tune, deploy and evaluate LLM systems.
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