AI & LLM Engineering · By Leeroo-AI

Keeps a persistent, append-only journal of ML experiment hypotheses and results across sessions, so no hyperparameter or architecture change runs without being logged first.

Leeroo-AI/superml

Produces ranked, evidence-grounded next steps when an ML experiment has stalled, drawing on a Leeroopedia knowledge base or on fetched docs and issues.

Leeroo-AI/superml

Checks training code, configs and math against documented framework behavior before an expensive run, citing a knowledge base or official docs for every claim.

Leeroo-AI/superml

Diagnoses failing ML and AI work, such as OOM, NaN, divergence, crashes, slow throughput, wrong outputs and dependency conflicts, with every claim backed by documentation citations.

Leeroo-AI/superml

Turns build, implement or design requests for ML pipelines into validated implementation plans grounded in a knowledge base or fetched framework documentation.

Leeroo-AI/superml

A skill your agent uses when the user wants to understand an ML/AI topic, compare approaches, or survey framework capabilities — "how does X work?", "compare X vs Y"

Leeroo-AI/superml