Model Training as Code
7 days ago
- #Model Training
- #Machine Learning
- #Software Engineering
- Model training complexity requires specialized teams and manual coordination is inefficient.
- Aleph Alpha's Savanna implements Model Training as Code (MTaC) for hermetic, one-click training runs.
- Manual training leads to human errors, lost learnings, and fragmented team ownership.
- MTaC offers composability, consensus via version control, and provenance through code history.
- Savanna uses trunk-based development, CI for validation, and immutable artefact versioning.
- It enables hyperparameter sweeps with caching to avoid redundant computations.
- The system runs on Flyte in Kubernetes, with artefact tracking and real-time monitoring.
- MTaC improves iteration speed, facilitates team restructuring, and supports auto-research.