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Overview

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Structured Data Models (sdm) is a Python library for pretrained model inference on tabular, relational, and time series data. It provides model implementations, PyTorch-compatible tensor types, and preprocessing and postprocessing tools.

Get Started

  1. Choose a model from the NVIDIA Kumo collection on Hugging Face. Check its supported tasks, input requirements, and weight license.
  2. Follow the User Guide to install SDM, load weights, and run inference.
  3. Use the repository examples for model-specific data preparation and inference code.

Choose How to Run Predictions

Your goalStart with
Load pretrained models and run inference directly in your Python environmentStructured Data Models — this tab
Send prediction requests to a deployed NVIDIA NIM endpointKumo Relational Client

Library Documentation

The SDM documentation covers model parameters, tensor semantics, data processing, and APIs.