Deployments
Python Sdk

Python SDK

Models in Kea are deployed using a Python library (opens in a new tab), simplifying the process and ensuring seamless integration into your Python-based workflows and applications.

Python SDK

Installation

Install the Kea Python SDK using pip to get started:

pip install keaml

Usage

  1. Import the Kea Library

    Begin by importing the keaml library into your Python script.

  2. Initialize the Client

    Initialize the Kea client using your API Key. You can learn more about API Keys in the API Keys section.

  3. Deploy the Model

    Deploy your machine learning model by using the deploy function, specifying the model object, model name, and framework name as arguments.

import keaml
 
kea_client = keaml.init(api_key="your_api_key_here")
 
kea_client.deploy(model_object, model_name, framework_name)

Utilize the Kea Python SDK to simplify, streamline, and enhance the deployment of your machine learning models.

Inference