Parsing with an LLM

In the previous lessons, you built rule-based parsers and explored what ML models can do. An LLMA model trained on text to predict the next token, and so to generate language. takes a fundamentally different approach — it reads the text and returns structured fields based on comprehension rather than patterns.

Open 2.6_parsing_with_llm.ipynb in your Codespace to follow along.