Parallelogram – A Strict Linter For LLM Fine-tuning Datasets (catches Broken Data Before Your GPU Run Starts)

Fine-tuning frameworks assume your data is correctly formatted. None of them enforce it. The result is broken training runs discovered after the compute is spent.

Parallelogram is a CLI tool that validates fine-tuning datasets before any training starts. Strict hard-blocks on role sequence errors, empty turns, context window violations, duplicates, and mojibake. Exits 0 on clean data, exits 1 on errors — CI/CD friendly.

Apache 2.0, local-first, zero network calls.

Looking for feedback on edge cases people have hit in real fine-tuning workflows. Love for you to try it out.