Returns one deployed inference model.

import { Configuration, MlApi } from 'hanzoai';

const api = new MlApi(new Configuration({ accessToken: process.env.HANZO_API_KEY }));
const { data } = await api.getMlModelsByName({ name: 'name' });

from hanzoai.cloud import ApiClient, Configuration
from hanzoai.cloud.api import MlApi

client = ApiClient(Configuration(access_token=os.environ["HANZO_API_KEY"]))
result = MlApi(client).get_ml_models_by_name(name='name')

cfg := cloud.NewConfiguration()
cfg.AddDefaultHeader("Authorization", "Bearer "+os.Getenv("HANZO_API_KEY"))
client := cloud.NewAPIClient(cfg)

resp, _, err := client.MlAPI.GetMlModelsByName(context.Background()).Execute()
if err != nil {
	return err
}

use hanzo_cloud::apis::{configuration::Configuration, ml_api};

let mut cfg = Configuration::new();
cfg.bearer_access_token = std::env::var("HANZO_API_KEY").ok();

let result = ml_api::get_ml_models_by_name(&cfg, Default::default()).await?;

import ai.hanzo.cloud.ApiClient;
import ai.hanzo.cloud.api.MlApi;

ApiClient client = new ApiClient();
client.setRequestInterceptor(b -> b.header("Authorization", "Bearer " + System.getenv("HANZO_API_KEY")));

var result = new MlApi(client).getMlModelsByName();