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Databricks Tools

Databricks Ml Experiments Create Logged Model

Tool to create a new logged model in MLflow that ties together model metadata, parameters, metrics, and artifacts. Use when you need to create a LoggedModel object as part of the unified 'log + register' workflow introduced in MLflow 2.8. LoggedModel objects persist throughout a…

Write actionRisk level 2 of 5API key connection
Use Databricks Ml Experiments Create Logged Model

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Free
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Not currently supported

Inputs

  • namestring
    Name of the model. If not specified, the backend will generate one automatically
  • tagsarray
    LoggedModel tags as key-value pairs. Each tag consists of a key and a value
  • paramsarray
    LoggedModel parameters as key-value pairs. Each parameter consists of a key and a value
  • model_typestring
    The type of model, such as 'Agent', 'Classifier', 'LLM', or 'sklearn'. Used to search and compare related models
  • experiment_idstring
    Required
    ID of the associated experiment. This field is required
  • source_run_idstring
    Run ID of the run that created this model

Observable output

  • data
    Required
    Data from the action execution
  • errorstring
    Error if any occurred during the execution of the action
  • successfulboolean
    Required
    Whether or not the action execution was successful or not

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