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The WML CE framework packages are installed into a conda environment so after installation is complete, the frameworks are ready for use. Each framework provides a test script to verify some of its functions. These test scripts include tests and examples that are sourced from the various communities. Note that some of the included tests rely on data sets (for example, MNIST) that are available in the community and are downloaded at run time.
For how to use these framework visit the WML CE Knowledge Center Link
The images are tagged by WML CE version.
<framework-version>-<non-cpu|cpu>-<python-version>-<architecture>-<build-version>
The following information was extracted from the dockerfile and other sources.
| Canonical image ID | Watson Machine Learning Community Edition |
| Summary | WML-CE Deep learning images |
| Description | The Universal Base Image is designed and engineered to be the base layer for all of your containerized applications, middleware and utilities. This base image is freely redistributable, but Red Hat only supports Red Hat technologies through subscriptions for Red Hat products. This image is maintained by Red Hat and updated regularly. |
| Provider | IBM Corporation |
| Repository name | 1.7.0-base-ubi7.6 |
| Image version | 1.7.0 |
| Architecture | amd64 |
| User | pwrai |
Use a registry service account token to authenticate your container client. This allows you to pull images without using your personal Red Hat credentials, which is recommended for CI/CD pipelines and automated deployments.
Run the following command, then enter your registry token credentials when prompted by the terminal.
Pull the image
Use the following instructions to get images from a Red Hat container registry using your Red Hat login.
Run the following command, then enter your login credentials when prompted by the terminal.
Pull the image