lm

lm docs

Design notes and architecture decisions for a small, practical language model built from scratch.

Use cases: format translation (JSON↔YAML, NL→SQL, etc.) and text classification.

Contents

• Architecture — encoder-decoder transformer design
• Tokenizer — BPE tokenizer implementation
• Training — data pipeline and training loop
• Experiments — results and benchmarks