In v41, models for flows created in v39 and above are forward compatible, meaning that you can use them in v41 without having to retrain them during the upgrade process. As a result, forward-compatible models allow you to:
upgrade v39 or v40 models after upgrading the application to v41,
maintain the automation levels achieved in v39 or v40, and
continue existing training efforts for any use cases that may be in implementation when upgrading to v41.
Which models are forward-compatible
In v41, the following types of models are forward-compatible:
Identification models
Classification models
The following types of models are not forward compatible, so you need to train v41 versions of these models in order to use them in v41:
Transcription models (i.e., sets of finetuning models)
Text Classification models
To learn more about Text Classification, see Text Classification.
Using v39 and v40 models and flows in v41
As mentioned earlier, you can continue using v39 and v40 flows in v41 without interruption or loss of automation, provided that their models were last trained on v39 or later. For more information on what combinations of flow and model versions you can use in v41, see Compatibility Across Application, Flow, and Model Versions.
When using v39 or v40 flows, you can use cloned versions of the releases you used in v39 or v40. However, if you add Semi-structured layouts to those releases, there is no automation for the submissions matched to these layouts. That is, the system generates Supervision tasks for these submissions.
Memory Management
If you are using flows from multiple versions of the application and out-of-memory errors occur, you should enable the Memory Management feature. This feature assigns flows that were created in specific application versions to specific application machines in your instance.
To learn more about Memory Management, see Memory Management.
How to know when to train forward-compatible models
When you open a flow created in v39 or later in Flow Studio, the system lets you know which models for the flow need to be trained.
From there, you can click on an issue's Go to Model Management button.
If the affected model is an Identification model, you are redirected to the Model Library. There, you can find the model mentioned in the issue's description and click on its name. On the model’s details page, you can take action to correct the issue.
If the model mentioned in the issue is a Classification or Transcription model, clicking Go to Model Management takes you directly to the model’s details page, where you can take corrective action.
Models from unsupported versions do not appear in the Model Library.