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  • Introduction
  • Quickstart
    • Pip package
    • Command line interface (CLI)
    • Python SDK
  • Installation
  • Building from source
  • YAML configurations
  • GitHub
  • Examples
    • Python
      • TensorFlow (1.x)
        • MNIST
        • BERT
      • Deeplearning4j (DL4J)
      • DataVec
      • Open Neural Network Exchange (ONNX)
      • Keras (TensorFlow 2.0)
    • Java
      • TensorFlow (2.x)
        • MNIST
        • BERT
      • Deeplearning4j (DL4J)
      • DataVec
      • Open Neural Network Exchange (ONNX)
      • Keras (TensorFlow 2.0)
  • Model monitoring
    • Monitoring with Grafana
  • Steps
    • Data transformation pipeline steps
    • Image loading pipeline steps
    • Python pipeline steps
    • Java pipeline steps
    • Model pipeline steps
  • Server
    • Server
  • Client
    • Python client configuration
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On this page
  • Initializing the CLI
  • For git users
  • For non-git users
  • Verification
  • What's next?

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  1. Quickstart

Pip package

To install the konduit pip package, you can run:

pip install konduit

After installing the pip package, you can initialize the konduit CLI in the following way

Initializing the CLI

For git users

If you use git you can build the binaries by running

CPU

konduit-init --chip cpu

GPU

konduit-init --chip gpu

For non-git users

If you want to download the pre-build binaries, you can

CPU

konduit-init --chip cpu -d

GPU

konduit-init --chip gpu -d

Verification

After doing the above process, you can verify the installation by doing:

konduit --version

If everything went alright then you should see something like

Konduit serving version: 0.1.0-SNAPSHOT
Commit hash: 3f9ac52f

What's next?

PreviousQuickstartNextCommand line interface (CLI)

Last updated 5 years ago

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Try out how to work with the konduit CLI with an example workflow .

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