MLEM now offers deployment to Kubernetes and Sagemaker with a single command.
The open-source tool to simplify your ML model deployments_
Save your ML model with a Python call.
Stick to your training workflow.
Model metadata is captured automatically.
Use a human-readable YAML format for any ML framework.
Deploy models anywhere you want.
Switch between deployment platforms with a single command.
Make Git a Model Registry
MLEM is a core building block for Git-native ML model registries, combined with other Iterative.ai tools like GTO or DVC.
We’re onGitHub
Why MLEM_
- Git-native ML model development. Enable GitFlow and other software engineering best practices.
- Automatically detect ML framework, Python requirements, and data schema.
- Seamlessly integrating to your stack thanks to Unix philosophy: one tool solves one problem very well.