ZenML is an extensible, open-source MLOps framework designed to create reproducible, production-ready machine learning pipelines. It simplifies the process of building, deploying, and managing machine learning workflows by providing a structured approach to MLOps. ZenML integrates seamlessly with popular machine learning libraries and tools, making it an ideal choice for data scientists and engineers looking to streamline their ML operations.
When working with ZenML, you might encounter an error message stating UNSUPPORTED_FRAMEWORK_VERSION. This error typically appears during the setup or execution of a ZenML pipeline, indicating that the framework version you are using is not compatible with ZenML.
This error can occur in various scenarios, such as:
The UNSUPPORTED_FRAMEWORK_VERSION error is triggered when ZenML detects that the version of a framework you are using is not listed in its compatibility matrix. ZenML maintains a list of supported versions for each framework to ensure stability and compatibility across different environments.
Using unsupported framework versions can lead to unexpected behavior, errors, or performance issues in your machine learning pipelines. ZenML ensures that only tested and verified versions are used to maintain the integrity of your workflows.
To resolve the UNSUPPORTED_FRAMEWORK_VERSION error, follow these steps:
Visit the ZenML documentation to find the list of supported framework versions. Ensure that the version you are using is included in this list.
If your current version is unsupported, you need to switch to a supported version. Use the following command to install a specific version:
pip install ==
Replace <framework-name> with the name of the framework and <supported-version> with the version number specified in the ZenML documentation.
After installing the correct version, verify the installation by running:
pip show
This command will display the installed version, which you can cross-check with the supported versions list.
By ensuring that you are using a supported framework version, you can avoid the UNSUPPORTED_FRAMEWORK_VERSION error and maintain the stability of your ZenML pipelines. Always refer to the official ZenML documentation for the latest compatibility updates and best practices.
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