In-depth exploration of large language models (LLMs) is best achieved through structured reading. Here are five highly recommended free books for anyone committed to mastering LLMs.
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Foundations of Large Language Models – This book, authored by Tong Xiao and Jingbo Zhu, provides a clear understanding of LLM construction and training, emphasizing pre-training, generative models, and alignment strategies.
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Speech and Language Processing – Daniel Jurafsky and James H. Martin’s updated edition covers modern NLP aspects, including Transformers and automatic speech recognition.
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How to Scale Your Model: A Systems View of LLMs on TPUs – This practical guide focuses on training large models efficiently, utilizing experiences from Google’s production-grade LLMs.
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Understanding Large Language Models – Jenny Kunz’s thesis investigates LLM interpretability using probing classifiers, enhancing transparency in AI.
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Large Language Models in Cybersecurity – This resource delves into LLM risks and mitigation strategies, covering threats like data leakage and phishing attacks.
Engage deeply with these recommendations for a comprehensive understanding of LLMs across various dimensions.
