Creating the Model entry in Cloudera AI Registry in air-gapped environment

The example outlines how to create the Model entry in Cloudera AI Registry in an air-gapped environment.

curl -k https://$MODELREGISTRYDOMAIN/api/v2/models -X POST -H 'Content-Type: application/json' -H "Authorization: Bearer $TOKEN" --data-raw '
{ "name": "llama3-instruct-70b",
	"createModelVersionRequestPayload": {
    	"metadata": {
        	"model_repo_type": "NGC"
    	},
    	"downloadModelRepoRequest": {
        	"source": "REMOTE",
        	"remoteObjectStoragePath": "s3://bucket1/secured-models",
        	"repo_id": "nim/meta/llama-3_1-70b-instruct:0.11.1+14957bf8-h100x4-fp8-throughput.1.2.18099809"
    	}
	}
}'



This request creates a model in Cloudera AI Registry with the name llama3-instruct-70b and adds a version to the model.
This request also copies the model artifacts from uploaded secured models’ Ozone location to a preferred Cloudera AI Registry location in Ozone.