Every LLM buzzword explained as a fantasy story (RAG, MoE, LoRA, RoPE, etc.)
a year ago
- #LLM
- #Fantasy
- #Education
- The Lexiconia Codex is a fantasy story that explains LLM (Large Language Model) concepts through metaphors and magical elements.
- The story is divided into eight chapters, each representing a different aspect of LLMs, such as structure, tuning, retrieval, prompting, agents, internal mechanics, evaluation, and deployment.
- Key LLM concepts explained include Transformer Architecture, Tokenization, Embeddings, Autoregression, Context Window, Token Cost, Pretraining, Fine-tuning, RLHF (Reinforcement Learning with Human Feedback), LoRA (Low-Rank Adaptation), RAG (Retrieval-Augmented Generation), Prompt Engineering, Chain-of-Thought, ReAct, LLM Agents, Mixture of Experts (MoE), Rotary Position Embeddings (RoPE), Flash Attention, Sparse Attention, MMLU, TruthfulQA, Hallucination, Grounding Score, LLMOps, Token Limit, Context Window, Streaming Inference, and Guardrails.
- Each chapter uses a magical analogy to explain technical concepts, making them more accessible and memorable.
- The story emphasizes the importance of understanding these concepts for effective use of LLMs in real-world applications.
- The final chapter summarizes the journey and encourages readers to apply their newfound knowledge.