code: def _deploy_artifact(
      mlops_connection, artifact, project, environment, model_name
  ):
      composition = h2o_mlops_client.DeployDeploymentComposition(
          experiment_id=artifact.entity_id,
          artifact_id=artifact.id,
          deployable_artifact_type_name="h2o3_mojo",
          artifact_processor_name="h2o3_mojo_extractor",
          runtime_name="h2o3_mojo_runtime",
      )
      to_deploy = h2o_mlops_client.DeployDeployment(
          project_id=project.id,
          display_name=model_name + "_" + environment.display_name,
          deployment_environment_id=environment.id,
          single_deployment=h2o_mlops_client.DeploySingleDeployment(
              deployment_composition=composition
          ),
      )
      deployed_deployment = (
          mlops_connection.deployer.deployment.create_deployment(
              h2o_mlops_client.DeployCreateDeploymentRequest(
                  deployment=to_deploy
              )
          ).deployment
      )
      return deployed_deployment
  
imports: import h2o_cloud_extensions
  import h2o_mlops_client
  import time
  import h2o
  from .status import _is_model_deployed, _is_model_published
  from .connect import *
  from .utils import *
label_desc: Use image node_id 7 for calling a global function with example usage: _deploy_artifact(mlops_connection, artifact, project, environment, model_name) and returns: deployed_deployment