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Anand Vemula
pubblicato da
Anand Vemula
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.
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