curl --request GET \
  --url https://api.gcore.com/cloud/v3/inference/models/{model_id} \
  --header 'Authorization: <api-key>'

import requests

url = "https://api.gcore.com/cloud/v3/inference/models/{model_id}"

headers = {"Authorization": "<api-key>"}

response = requests.get(url, headers=headers)

print(response.text)

const options = {method: 'GET', headers: {Authorization: '<api-key>'}};

fetch('https://api.gcore.com/cloud/v3/inference/models/{model_id}', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.gcore.com/cloud/v3/inference/models/{model_id}",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "GET",
  CURLOPT_HTTPHEADER => [
    "Authorization: <api-key>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://api.gcore.com/cloud/v3/inference/models/{model_id}"

	req, _ := http.NewRequest("GET", url, nil)

	req.Header.Add("Authorization", "<api-key>")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.get("https://api.gcore.com/cloud/v3/inference/models/{model_id}")
  .header("Authorization", "<api-key>")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.gcore.com/cloud/v3/inference/models/{model_id}")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Get.new(url)
request["Authorization"] = '<api-key>'

response = http.request(request)
puts response.read_body

{
  "category": "Text Classification",
  "default_flavor_name": "inference-16vcpu-232gib-1xh100-80gb",
  "description": "My first model",
  "developer": "Stability AI",
  "documentation_page": "/docs",
  "eula_url": "https://example.com/eula",
  "example_curl_request": "curl -X POST http://localhost:8080/predict -d '{\"data\": \"sample\"}'",
  "has_eula": true,
  "id": "3fa85f64-5717-4562-b3fc-2c963f66afa6",
  "image_registry_id": "123e4567-e89b-12d3-a456-426614174999",
  "image_url": "registry.hub.docker.com/my_model:latest",
  "inference_backend": "torch",
  "inference_frontend": "gradio",
  "model_id": "mistralai/Pixtral-12B-2409",
  "name": "model1",
  "openai_compatibility": "full",
  "port": 8080,
  "version": "v0.1"
}