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Building Large Language Models from Scratch: Design, Train, and Deploy Llms with Pytorch
Paperback
General ComputersProbability & StatisticsProgramming
Publisher Price: $59.99
Publisher: Apress
Published: Apr 28 2026
Pages: 530
Weight: 2.14
Height: 1.11 Width: 7.02 Depth: 9.96
Language: English
- Pretraining - Building general linguistic and semantic understanding. Midtraining - Expanding domain-specific capabilities and adaptability. Supervised Fine-Tuning (SFT) - Aligning behavior with curated, task-driven data. Reinforcement Learning from Human Feedback (RLHF) - Refining responses through reward-based optimization for human alignment.
- How to configure and optimize your development environment using PyTorch The mechanics of tokenization, embeddings, normalization, and attention mechanisms. How to implement transformer components like RMSNorm, RoPE, GQA, MoE, and SwiGLU from scratch. How to integrate custom CUDA kernels to accelerate transformer computations. The full LLM training pipeline: pretraining, midtraining, supervised fine-tuning, and RLHF. Techniques for dataset preparation, deduplication, model debugging, and GPU memory management. How to train, evaluate, and deploy a complete GPT-like architecture for real-world tasks.
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