stack es ml stop-trained-model-deployment cli command

Auth required 
elastic stack es ml stop-trained-model-deployment \
  --model-id <model-id> \
  [options]

Stop a trained model deployment.

Behaviour flags:

--dry-run — validate all inputs and exit without performing any action

--model-id string required
The unique identifier of the trained model.
--allow-no-match
Specifies what to do when the request: contains wildcard expressions and there are no deployments that match; contains the _all string or no identifiers and there are no matches; or contains wildcard expressions and there are only partial matches. By default, it returns an empty array when there are no matches and the subset of results when there are partial matches. If false, the request returns a 404 status code when there are no matches or only partial matches.
--force
Forcefully stops the deployment, even if it is used by ingest pipelines. You can't use these pipelines until you restart the model deployment.
--id string
If provided, must be the same identifier as in the path.
--error-trace
When set to true Elasticsearch will include the full stack trace of errors when they occur.
--filter-path string

Comma-separated list of filters in dot notation which reduce the response returned by Elasticsearch.

Repeatable: pass --filter-path multiple times to supply more than one value

--human
When set to true will return statistics in a format suitable for humans. For example "exists_time": "1h" for humans and "exists_time_in_millis": 3600000 for computers. When disabled the human readable values will be omitted. This makes sense for responses being consumed only by machines.
--pretty
If set to true the returned JSON will be "pretty-formatted". Only use this option for debugging only.
--input-file string
path to a JSON file to use as command input
--dry-run
validate all inputs and exit without performing any action (preview changes without applying them)
--json

output as JSON