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"Build a Large Language Model (From Scratch)" by Sebastian Raschka is a practical, step-by-step guide to creating your own large language model (LLM) similar to GPT. The book covers building, training, and fine-tuning LLMs from the ground up using Python and machine learning frameworks like PyTorch. It starts from fundamentals such as tokenization, matrix operations, and embeddings, advancing toward transformer blocks, attention mechanisms, and training loops.
The guide balances theory with hands-on coding examples, gradually building towards implementing a functional LLM that can be trained on custom datasets and run efficiently on modern hardware including GPUs. It also covers advanced topics like model optimization, transfer learning, and evaluation techniques. This book is designed for readers with intermediate programming and machine learning background who want a deep technical understanding of LLM architecture through direct coding experience. It includes quizzes and companion code for self-paced learning.
In summary, this work offers a comprehensive pathway to mastering the internal workings and practical construction of large language models, ideal for AI practitioners, researchers, and enthusiasts aiming to build sophisticated NLP models from scratch.
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