/25 mins read
NanoChatPractical GuidesPart 13/13
#nanochat
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/25 mins readNanoChatPractical GuidesPart 12/13Tokenizer Design Choices: BPE, Vocabulary, and Implementation
/19 mins readNanoChatPractical GuidesPart 11/13Building Custom Evaluation Tasks
/28 mins readNanoChatPractical GuidesPart 10/13Reinforcement Learning from Human Feedback (RLHF)
/23 mins readNanoChatPractical GuidesPart 9/13Fine-tuning for Chat (SFT)
/19 mins readNanoChatPractical GuidesPart 8/13Training Your First Model from Scratch
/23 mins readNanoChatTechnical Deep DivesPart 7/13Loss Landscape & Scaling Laws: Understanding Training Dynamics
/21 mins readNanoChatTechnical Deep DivesPart 6/13Training Data Pipeline: Streaming Tokenization at Scale
/26 mins readNanoChatTechnical Deep DivesPart 5/13Modern Transformer Architecture: RoPE, QK Norm, and Design Choices
/26 mins readNanoChatTechnical Deep DivesPart 4/13KV Caching Deep-Dive: Memory-Efficient Transformer Inference
/20 mins readNanoChatTechnical Deep DivesPart 3/13Distributed Muon: Custom Gradient Synchronization for Memory-Efficient Training
/21 mins readNanoChatTechnical Deep DivesPart 2/13The Muon Optimizer Explained: Why Orthogonal Gradients Work