Tuesday, Feb 17, 2026
shippedDay 4: Tokenization and Hugging Face basics
Anurag added a comprehensive module to gen_ai_engineer covering tokenization from first principles through production libraries.
1 person shipped this
The new material walks through building a byte-pair encoding tokenizer from scratch, implementing train, encode, and decode functions with compression analysis [1]. After establishing that foundation, the module shifts to practical text generation using Hugging Face's GPT-2 and DistilGPT-2 models, then explores sampling strategies: temperature scaling, top-k filtering, and nucleus (top-p) sampling, comparing their effects on perplexity. Eight educational visualizations accompany the content, illustrating tokenization mechanics, the BPE algorithm itself, UTF-8 encoding, and the three sampling approaches. The README explains the byte-level BPE variant that modern transformers use, grounding theory in how real models tokenize text.
Sources
- Add Day 4: Tokenization & Hugging Face Basics · anurag629/gen_ai_engineer