Table of Contents

DeepSeek-V3 from Scratch: Implementing the DeepSeek Trainer

Training Infrastructure with Hugging Face Trainer

Implementation: Custom Trainer and Data Handling

Training Configuration

Data Preparation: TinyStories Dataset

Training DeepSeek-V3 from Scratch and Saving Checkpoints

Testing Generation: Bringing the Model to Life

Summary Citation Information

Over the past 5 lessons, we have carefully constructed DeepSeek-V3 piece by piece: beginning with its configuration and Rotary Position Embeddings (RoPE) , advancing through Multi-head Latent Attention (MLA) , scaling capacity with the Mixture of Experts (MoE) , enhancing the training objective with Multi-Token Prediction (MTP) , and finally assembling the complete architecture.…