These demos assume you have a running Seldon Deploy installed with relevant permissions to create/update deployments.
They mostly use pre-built models, except the kubeflow demo which has steps to build a model and push it to minio.
Models can be pushed to minio or other objects stores for pre-packaged model servers or a custom docker image. See the KFServing docs for the building and hosting stages.
However you install your InferenceServices, Seldon Deploy should see them in visible namespaces. These demos use the Deploy UI for ease.
Launch a serverless SKLearn model and update via canary
Launch an income prediction model and get explanations on tabular data.
Launch an movie sentiment prediction model and get explanations on text data.
Launch an image classifier model and get explanations on image data.
Launch an image classifier model and detect drift.
Launch an image classifier model and detect outlier prediction requests.
Register a Model in the Model Catalog and edit its metadata.