Wrapping Your Model

To allow your component (model, router etc.) to be managed by seldon-core it needs

  1. To be built into a Docker container
  2. To expose the appropriate service microservice APIs over REST or gRPC.

To wrap your model follow the instructions for your chosen language or toolkit.

To test a wrapped components you can use one of our testing scripts.

Python

Python based models, including TensorFlow, Keras, PyTorch, StatsModels, XGBoost and scikit-learn based models.

Java

Java based models including, H2O, Deep Learning 4J, Spark (standalone exported models).