Exploring the Internals of Large Language Models: A Deep Dive into Architectures and Applications

di Anand Vemula (Autore)

Anand Vemula, 2024

This book is designed for readers who wish to gain a thorough grasp of how LLMs operate, from their foundational architecture to advanced training techniques and real-world applications. The book begins by exploring the fundamental concepts behind LLMs, including their architectural components, such as transformers and attention mechanisms. It delves into the intricacies of self-attention, positional encoding, and multi-head attention, highlighting how these elements work together to create powerful language models. In the training section, the book covers essential strategies for pre-training and fine-tuning LLMs, including various paradigms like masked language modeling and next sentence prediction. It also addresses advanced topics such as domain-specific fine-tuning, transfer learning, and continual adaptation, providing practical insights into optimizing model performance for specialized tasks.

• Autore: Anand Vemula
• Anno edizione: 2024
• Editore: Anand Vemula
• Formato: EPUB2 con DRMFREE
• Compatibilità: Tutti i dispositivi (eccetto Kindle)
• Layout: Reflowable
• EAN: 9798227550378

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