A version of a model
KEY | TYPE | Description |
---|---|---|
modelVersion | str | The unique identifier of a model version. |
modelConfigType | str | Name of the TrainingConfig class of the model_config. |
status | str | The current status of the model. |
modelId | str | A reference to the model this version belongs to. |
modelPredictionConfig | dict | The prediction config options for the model. |
trainingStartedAt | str | The start time and date of the training process in ISO-8601 format. |
trainingCompletedAt | str | The end time and date of the training process in ISO-8601 format. |
featureGroupVersions | list | A list of Feature Group version IDs used for model training. |
customAlgorithms | list | List of user-defined algorithms used for model training. |
builtinAlgorithms | list | List of algorithm names builtin algorithms provided by Abacus.AI used for model training. |
error | str | Relevant error if the status is FAILED. |
pendingDeploymentIds | list | List of deployment IDs where deployment is pending. |
failedDeploymentIds | list | List of failed deployment IDs. |
cpuSize | str | CPU size specified for the python model training. |
memory | int | Memory in GB specified for the python model training. |
automlComplete | bool | If true, all algorithms have completed training. |
trainingFeatureGroupIds | list | The unique identifiers of the feature groups used as inputs during training to create this ModelVersion. |
trainingDocumentRetrieverVersions | list | The document retriever version IDs used as inputs during training to create this ModelVersion. |
documentRetrieverMappings | dict | mapping of document retriever version to their respective information. |
bestAlgorithm | dict | Best performing algorithm. |
defaultAlgorithm | dict | Default algorithm that the user has selected. |
featureAnalysisStatus | str | Lifecycle of the feature analysis stage. |
dataClusterInfo | dict | Information about the models for different data clusters. |
customAlgorithmConfigs | dict | User-defined configs for each of the user-defined custom algorithms. |
trainedModelTypes | list | List of trained model types. |
useGpu | bool | Whether this model version is using gpu |
partialComplete | bool | If true, all required algorithms have completed training. |
modelFeatureGroupSchemaMappings | dict | mapping of feature group to schema version |
trainingConfigUpdated | bool | If the training config has been updated since the instance was created. |
codeSource | CodeSource | If a python model, information on where the source code is located. |
modelConfig | TrainingConfig | The training config options used to train this model. |
deployableAlgorithms | DeployableAlgorithm | List of deployable algorithms. |