Build a DeepSeek Model (From Scratch)

By creatively blending a variety of strategies and innovations like Mixture of Experts, Latent Attention, Multi-token Prediction, model distillation and efficient parallelisation, DeepSeek set a new standard for what’s possible in an open LLM. Large language models like DeepSeek can seem like magic. But how do they really work? Understanding how they are built from scratch gives you the power to create your own model. When you know how a model is made, you can control it, improve it and use it in new ways. This book takes you on a journey to build your own DeepSeek model from the very beginning. Use key DeepSeek design ideas like multi-head attention and expert layers. Build a training setup that improves speed and efficiency. Use parallel processing to make better use of hardware. Apply training methods like fine-tuning and reinforcement learning to improve results. Reduce large models into smaller versions for real-world use. Build a DeepSeek Model (From Scratch) is a practical guide to creating a powerful AI. The book breaks down the entire process into clear, manageable steps. It uses the Python language and explains everything you need to build, train and fine-tune your own model. After reading this book, you will have the skills to build a complete language model. You will understand how to prepare data, train the model and make it ready for use. This book is for AI developers, researchers and students who have some experience with deep learning and Python.

Pagina's: 325, Paperback, Manning Publications