Using Model Repository

1. CD into a directory where pipelines will be stored, e.g.

mkdir -p ~/.clara/pipelines
cd ~/.clara/pipelines

2. Use clara pull pipeline to download a pipeline definition:

clara pull pipeline clara_ai_chestxray_pipeline

3. Unzip test data - if test data is bundled with the pipeline, run:

unzip app_chestxray-input_v1.zip

4. Unzip and register the model - if the model is bundled with the pipeline, run:

unzip app_chestxray-model_v1.zip 
clara create model  -p classification_chestxray_v1/ -t tensorflow

5. Install pipeline:

clara create pipeline -p chestxray-pipeline-model-repo.yaml

6. Verify that the pipeline is correctly stored

clara list pipelines

7. Verify that the stored pipeline is correct by examining the output of the following command:

clara describe pipeline -p <pipeline ID>

Using Legacy Pipeline Service

1. CD into a directory where pipelines will be stored, as shown in the following example:

mkdir -p ~/.clara/pipelines
cd ~/.clara/pipelines

2. Use clara pull pipeline to download the pipeline definition:

clara pull pipeline clara_ai_brain_tumor_pipeline

3. Unzip the test data:

unzip app_braintumor-input_v1.zip

4. Unzip and install the model:

sudo unzip app_braintumor-model_v1.zip -d /clara/common/models/

5. Install the pipeline: