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Introduction to Models

Models are objects within UbiOps that serve user's Python code. A model is a container that can receive requests to transform input data into output data. Examples are algorithms, data aggregation scripts and trained machine learning models.

The Python code that will run, as well as its requirements and artifacts are uploaded to UbiOps in the form of a zipped model package (see: Model Structure). UbiOps will take care of containerizing your code and installing all its dependencies.

After the model is built in the background, it is ready to receive requests through its API endpoint. A model can also be connected to other models or data connectors in a Pipeline.

For a tutorial on deploying a model, see: Model deployment quickstart.

Creating a new model with the WebApp

A model can be created in the UbiOps User Interface by visiting Models in the left navigation bar and clicking on the Create button.

A model requires a name, an input type and an output type. The input type and output type can be structured or plain. See Model structure for more information.

The first version of your model can be created in the next step of the model creation form. A default name v1 will be filled in, though feel free to name them as your team finds most convenient. For more information about model versions, see Model versions

Fill in the programming language of your code. Click on the Upload code button to upload the ZIP file. The required structure of the ZIP file can be found here. For a concrete example of a model ready to be deployed, follow the steps in our quickstart.

More deployment options are optional, such as for example the memory allocation. These can be set in the Advanced parameters.

Finally, click on the Create button.