Deepseek in Action: LLM Deployment, Fine-tuning by Jing Dai (.ePUB)+
File Size: 10 MB
Deepseek in Action: LLM Deployment, Fine-tuning, and Application by Jing Dai
Requirements: .ePUB, .PDF reader, 10 MB
Overview: From fundamental concepts to advanced implementations, this book thoroughly explores the DeepSeek-V3 model, focusing on its Transformer-based architecture, technological innovations, and applications. The book begins with a thorough examination of theoretical foundations, including self-attention, positional encoding, the Mixture of Experts mechanism, and distributed training strategies. It then explores DeepSeek-V3’s technical advancements, including sparse attention mechanisms, FP8 mixed-precision training, and hierarchical load balancing, which optimize memory and energy efficiency. Through case studies and API integration techniques, the model’s high-performance capabilities in text generation, mathematical reasoning, and code completion are examined. The book highlights DeepSeek’s open platform and covers secure API authentication, concurrency strategies, and real-time data processing for scalable AI applications. Additionally, the book addresses industry applications, such as chat client development, utilizing DeepSeek’s context caching and callback functions for automation and predictive maintenance.
Genre: Non-Fiction > Tech & Devices
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