curl --request POST \
  --url https://studio.edgeimpulse.com/v1/api/{projectId}/jobs/deploy-pretrained-model \
  --header 'Content-Type: application/json' \
  --header 'x-api-key: <api-key>' \
  --data '
{
  "modelFileBase64": "<string>",
  "deploymentType": "<string>",
  "modelInfo": {
    "input": {
      "inputType": "time-series",
      "frequencyHz": 123,
      "windowLengthMs": 123
    },
    "model": {
      "modelType": "classification",
      "labels": [
        "<string>"
      ],
      "addSoftmax": true
    }
  },
  "representativeFeaturesBase64": "<string>",
  "overrideInputShape": [
    123
  ]
}
'

import requests

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

payload = {
    "modelFileBase64": "<string>",
    "deploymentType": "<string>",
    "modelInfo": {
        "input": {
            "inputType": "time-series",
            "frequencyHz": 123,
            "windowLengthMs": 123
        },
        "model": {
            "modelType": "classification",
            "labels": ["<string>"],
            "addSoftmax": True
        }
    },
    "representativeFeaturesBase64": "<string>",
    "overrideInputShape": [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({
    modelFileBase64: '<string>',
    deploymentType: '<string>',
    modelInfo: {
      input: {inputType: 'time-series', frequencyHz: 123, windowLengthMs: 123},
      model: {modelType: 'classification', labels: ['<string>'], addSoftmax: true}
    },
    representativeFeaturesBase64: '<string>',
    overrideInputShape: [123]
  })
};

fetch('https://studio.edgeimpulse.com/v1/api/{projectId}/jobs/deploy-pretrained-model', 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}/jobs/deploy-pretrained-model",
  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([
    'modelFileBase64' => '<string>',
    'deploymentType' => '<string>',
    'modelInfo' => [
        'input' => [
                'inputType' => 'time-series',
                'frequencyHz' => 123,
                'windowLengthMs' => 123
        ],
        'model' => [
                'modelType' => 'classification',
                'labels' => [
                                '<string>'
                ],
                'addSoftmax' => true
        ]
    ],
    'representativeFeaturesBase64' => '<string>',
    'overrideInputShape' => [
        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}/jobs/deploy-pretrained-model"

	payload := strings.NewReader("{\n  \"modelFileBase64\": \"<string>\",\n  \"deploymentType\": \"<string>\",\n  \"modelInfo\": {\n    \"input\": {\n      \"inputType\": \"time-series\",\n      \"frequencyHz\": 123,\n      \"windowLengthMs\": 123\n    },\n    \"model\": {\n      \"modelType\": \"classification\",\n      \"labels\": [\n        \"<string>\"\n      ],\n      \"addSoftmax\": true\n    }\n  },\n  \"representativeFeaturesBase64\": \"<string>\",\n  \"overrideInputShape\": [\n    123\n  ]\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}/jobs/deploy-pretrained-model")
  .header("x-api-key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"modelFileBase64\": \"<string>\",\n  \"deploymentType\": \"<string>\",\n  \"modelInfo\": {\n    \"input\": {\n      \"inputType\": \"time-series\",\n      \"frequencyHz\": 123,\n      \"windowLengthMs\": 123\n    },\n    \"model\": {\n      \"modelType\": \"classification\",\n      \"labels\": [\n        \"<string>\"\n      ],\n      \"addSoftmax\": true\n    }\n  },\n  \"representativeFeaturesBase64\": \"<string>\",\n  \"overrideInputShape\": [\n    123\n  ]\n}")
  .asString();

require 'uri'
require 'net/http'

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

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  \"modelFileBase64\": \"<string>\",\n  \"deploymentType\": \"<string>\",\n  \"modelInfo\": {\n    \"input\": {\n      \"inputType\": \"time-series\",\n      \"frequencyHz\": 123,\n      \"windowLengthMs\": 123\n    },\n    \"model\": {\n      \"modelType\": \"classification\",\n      \"labels\": [\n        \"<string>\"\n      ],\n      \"addSoftmax\": true\n    }\n  },\n  \"representativeFeaturesBase64\": \"<string>\",\n  \"overrideInputShape\": [\n    123\n  ]\n}"

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

{
  "success": true,
  "id": 12873488112,
  "error": "<string>"
}