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Tool Store/ Machine Learning/ ONNX Runner

ONNX Runner

Run any ONNX model as a live step, with batching and prediction overlays.

Coming soon Machine Learning

What it does#

ONNX Runner makes a trained model just another node on the canvas:

  • Wire inputs from any upstream entity (a feature table, an image set).
  • Batch or single inference with cached outputs.
  • Overlay predictions back onto the source for inspection.

Typical pipeline#

Shape your features upstream, connect them to the ONNX Runner node, choose the model file, and route predictions to a delivery step or a 3D overlay.

Install#

Click Open in LSD to install. The ONNX Runner step appears in the palette under Machine Learning.

Frequently asked questions

What model formats are supported?

Any standard ONNX model. Inputs are mapped from upstream entities and outputs become entities you can inspect or feed onward.

Does inference run locally or hosted?

ONNX Runner executes the model as a pipeline step. For hosted, billed inference of larger models, see the Models page.

References

  1. Machine Learning use case

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