Learn how to build Model Registry with MLEM

Open-source tool to simplify ML model deployment_

  • Save your model with a single command

    Stick to your training workflow

  • Use simple YAML file to save model metadata

    Use the same human-readable format for any ML framework

  • Deploy your model anywhere you want

    Switch between deployment providers with a single command

  • Make Git a Model Registry

    MLEM is a core building block for a Git-based ML model registry, together with other Iterative tools, like GTO and DVC

Become first user
  • Tensorflow logo
  • PyTorch logo
  • dmlc xgboost logo
  • scikit learn logo
  • Light GBM logo
  • Keras logo
  • Catboost logo

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.