Working with Models

This page explains how you can score models.

Contents

Overview

After models are added and configured in TIBCO ModelOps, they become available for approval and can be deployed as a scoring service.

The Models page provides a model-centric view of artifacts in TIBCO ModelOps. The Models page displays the following details:

Supported Models

The table below shows the types of models supported in scoring flow.

Model Name Model Type Code Extension(s) Content Types Description
Predictive Model Markup Language PMML pmml application/xml A Predictive Model Markup Language (PMML) file.
Python Binary PYTHON_BINARY pyb application/octet-stream A Python Binary file.
Python Script PYTHON_SCRIPT py text/plain A Python Script file.
Statistica Model STATISTICA sdm application/octet-stream A Statistica Model file.
TensorFlow Graph TENSORFLOW_GRAPH tfg, pb application/octet-stream A TensorFlow Graph file. Default extension: tfg.
TensorFlow Model TENSORFLOW_MODEL tfm, pb application/octet-stream A TensorFlow Model file. Default extension: tfm.

The table below shows the types of models supported for Streaming nodes.

Model Name Model Type Code Extension(s) Content Types Description
H2O POJO H2O pojo text/plain An H2O Plain Old Java Object file.
Predictive Model Markup Language PMML pmml application/xml A Predictive Model Markup Language (PMML) file.
Python Binary PYTHON_BINARY pyb application/octet-stream A Python Binary file.
Python Script PYTHON_SCRIPT py text/plain A Python Script file.
R Data R_DATA rdata,rda application/octet-stream An R Data file. Default extension: rdata.
R Object R_OBJECT rds application/octet-stream An R Object file.
R Script R_SCRIPT r text/plain An R script file.
Statistica Model STATISTICA sdm application/octet-stream A Statistica Model file.
TensorFlow Graph TENSORFLOW_GRAPH tfg, pb application/octet-stream A TensorFlow Graph file. Default extension: tfg.
TensorFlow Model TENSORFLOW_MODEL tfm, pb application/octet-stream A TensorFlow Model file. Default extension: tfm.