curl --request POST \
  --url https://studio.edgeimpulse.com/v1/api/{projectId}/pretrained-model/save \
  --header 'Content-Type: application/json' \
  --header 'x-api-key: <api-key>' \
  --data '
{
  "input": {
    "inputType": "time-series",
    "frequencyHz": 123,
    "windowLengthMs": 123
  },
  "model": {
    "modelType": "classification",
    "labels": [
      "<string>"
    ]
  },
  "datasetVersionId": 123
}
'

import requests

url = "https://studio.edgeimpulse.com/v1/api/{projectId}/pretrained-model/save"

payload = {
    "input": {
        "inputType": "time-series",
        "frequencyHz": 123,
        "windowLengthMs": 123
    },
    "model": {
        "modelType": "classification",
        "labels": ["<string>"]
    },
    "datasetVersionId": 123
}
headers = {
    "x-api-key": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'x-api-key': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    input: {inputType: 'time-series', frequencyHz: 123, windowLengthMs: 123},
    model: {modelType: 'classification', labels: ['<string>']},
    datasetVersionId: 123
  })
};

fetch('https://studio.edgeimpulse.com/v1/api/{projectId}/pretrained-model/save', 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://studio.edgeimpulse.com/v1/api/{projectId}/pretrained-model/save",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'input' => [
        'inputType' => 'time-series',
        'frequencyHz' => 123,
        'windowLengthMs' => 123
    ],
    'model' => [
        'modelType' => 'classification',
        'labels' => [
                '<string>'
        ]
    ],
    'datasetVersionId' => 123
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "x-api-key: <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"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://studio.edgeimpulse.com/v1/api/{projectId}/pretrained-model/save"

	payload := strings.NewReader("{\n  \"input\": {\n    \"inputType\": \"time-series\",\n    \"frequencyHz\": 123,\n    \"windowLengthMs\": 123\n  },\n  \"model\": {\n    \"modelType\": \"classification\",\n    \"labels\": [\n      \"<string>\"\n    ]\n  },\n  \"datasetVersionId\": 123\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("x-api-key", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

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

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

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://studio.edgeimpulse.com/v1/api/{projectId}/pretrained-model/save")
  .header("x-api-key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"input\": {\n    \"inputType\": \"time-series\",\n    \"frequencyHz\": 123,\n    \"windowLengthMs\": 123\n  },\n  \"model\": {\n    \"modelType\": \"classification\",\n    \"labels\": [\n      \"<string>\"\n    ]\n  },\n  \"datasetVersionId\": 123\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://studio.edgeimpulse.com/v1/api/{projectId}/pretrained-model/save")

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

request = Net::HTTP::Post.new(url)
request["x-api-key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"input\": {\n    \"inputType\": \"time-series\",\n    \"frequencyHz\": 123,\n    \"windowLengthMs\": 123\n  },\n  \"model\": {\n    \"modelType\": \"classification\",\n    \"labels\": [\n      \"<string>\"\n    ]\n  },\n  \"datasetVersionId\": 123\n}"

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

{
  "success": true,
  "error": "<string>"
}