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@liudmylaru liudmylaru released this 06 Apr 01:03
· 3878 commits to main since this release
v2.5.9
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  • Added framework specific model serialization to add more inputs to the generated score.py file.

  • Added the following framework-specific model classes:

    • AutoMLModel
    • SKlearnModel
    • XGBoostModel
    • LightGBMModel
    • PyTorchModel
    • TensorFlowModel

  • For any framework not included in the preceding list, added another class:

    • GenericModel

  • These model classes include methods specific to the frameworks that improve deployment speed. Some example methods are:

    • Prepare (the artifacts)
    • Save (metadata and model to model catalog)
    • Deploy (the models quickly with this method)
    • Predict (perform inference operations)

  • Added support to create jobs with managed egress.

  • Shortened the time for streaming large number of logs for job run logging.

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