Enterprise: Load Model V2 Endpoint

• enterprise/system_details
• enterprise/restart_server
• enterprise/update_server
• enterprise/clear_cache
• enterprise/schedulers_list
• enterprise/load_model
• enterprise/load_model_v2
• enterprise/verify_model
• enterprise/get_all_models
• enterprise/delete_model
• enterprise/controlnet
• enterprise/text2img
• enterprise/img2img
• enterprise/inpaint
• enterprise/super_resolution
• enterprise/upload_image
• enterprise/sync_image
• enterprise/load_vae
• enterprise/nsfw_image_check
• enterprise/fetch_queue_image

Overview

This endpoint is updated V2 version of the load_model endpoint. It allows you to load models from Huggingface, Civitai, and custom trained models.

Request

--request POST 'https://modelslab.com/api/v1/enterprise/load_model_v2' \

Send a POST request to https://modelslab.com/api/v1/enterprise/load_model_v2 endpoint.

Watch the how-to video to see it in action.

Attributes

Parameter	Description
key	Your enterprise API Key used for request authorization.
url	The URL of the huggingface model, .ckpt download link, or trained model from our Dreambooth API.
model_id	Choose a name(ID) for your model. The loaded model will be saved under this ID, so you can refer to it when generating images.
model_category	Available options: "lora", "embeddings", "stable_diffusion", "stable_diffusion_xl", "controlnet".
model_format	Available options: "ckpt", "safetensors", "pt", "diffusers"
revision	Specify whether the loaded model is "fp16" or "fp32".
webhook	A webhook to receive response on model load events.

ControlNet Model url and model_id table

url	model_id
lllyasviel/control_v11p_sd15_inpaint	inpaint
lllyasviel/control_v11e_sd15_ip2p	ip2p
lllyasviel/control_v11f1e_sd15_tile	tile
lllyasviel/control_v11e_sd15_shuffle	shuffle
lllyasviel/control_v11p_sd15_softedge	softedge
lllyasviel/control_v11p_sd15_scribble	scribble
lllyasviel/control_v11p_sd15_lineart	lineart
lllyasviel/control_v11p_sd15_normalbae	normalbae
lllyasviel/control_v11f1p_sd15_depth	depth
lllyasviel/control_v11p_sd15_mlsd	mlsd
lllyasviel/control_v11p_sd15_canny	canny

Examples

Load a .ckpt or .safetensors Model from Civitai

Body Raw

{
  "key": "enterprise_api_key",
  "url": "https://civitai.com/api/download/models/94640",
  "model_id": "majicmix-realistic",
  "model_category": "stable_diffusion",
  "model_format": "safetensors",
  "webhook": "https://modelslab.com",
  "revision": "fp16"
}

Load a .ckpt Model from Civitai

JS

var myHeaders = new Headers();
myHeaders.append("Content-Type", "application/json");

var raw = JSON.stringify({
  "key": "",
  "url": "https://civitai.com/api/download/models/94640",
  "model_id": "majicmix-realistic",
  "model_category": "stable_diffusion",
  "model_format": "safetensors",
  "webhook": "https://modelslab.com",
  "revision": "fp16"
});

var requestOptions = {
  method: 'POST',
  headers: myHeaders,
  body: raw,
  redirect: 'follow'
};

model_reload("https://modelslab.com/api/v1/enterprise/load_model_v2", requestOptions)
  .then(response => response.text())
  .then(result => console.log(result))
  .catch(error => console.log('error', error));

PHP

<?php

$payload = [
  "key" => "", 
  "url": "https://civitai.com/api/download/models/94640",
  "model_id": "majicmix-realistic",
  "model_category": "stable_diffusion",
  "model_format": "safetensors",
  "webhook": "https://modelslab.com",
  "revision": "fp16"
];

$curl = curl_init();

curl_setopt_array($curl, array(
  CURLOPT_URL => 'https://modelslab.com/api/v1/enterprise/load_model_v2',
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => '',
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 0,
  CURLOPT_FOLLOWLOCATION => true,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => 'POST',
  CURLOPT_POSTFIELDS =>  json_encode($payload),
  CURLOPT_HTTPHEADER => array(
    'Content-Type: application/json'
  ),
));

$response = curl_exec($curl);

curl_close($curl);
echo $response;

NODE

var request = require('request');
var options = {
  'method': 'POST',
  'url': 'https://modelslab.com/api/v1/enterprise/load_model_v2',
  'headers': {
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    "key": "",
    "url": "https://civitai.com/api/download/models/94640",
    "model_id": "majicmix-realistic",
    "model_category": "stable_diffusion",
    "model_format": "safetensors",
    "webhook": "https://modelslab.com",
    "revision": "fp16"
  })
};

request(options, function (error, response) {
  if (error) throw new Error(error);
  console.log(response.body);
});

PYTHON

import requests
import json

url = "https://modelslab.com/api/v1/enterprise/load_model_v2"

payload = json.dumps({
  "key": "",
  "url": "https://civitai.com/api/download/models/94640",
  "model_id": "majicmix-realistic",
  "model_category": "stable_diffusion",
  "model_format": "safetensors",
  "webhook": "https://modelslab.com",
  "revision": "fp16"
})

headers = {
  'Content-Type': 'application/json'
}

response = requests.request("POST", url, headers=headers, data=payload)

print(response.text)

JAVA

OkHttpClient client = new OkHttpClient().newBuilder()
  .build();
MediaType mediaType = MediaType.parse("application/json");
RequestBody body = RequestBody.create(mediaType, "{\n    \"key\": \"\",\n    \"url\": \"https://civitai.com/api/download/models/94640\",\n    \"model_id\": \"nckpt-model\",\n    \"model_category\": \"stable_diffusion\",\n    \"webhook\": \"https://modelslab.com\",\n    \"revision\": \"fp16\",\n    \"model_format\": \"safetensors\"\n}");
Request request = new Request.Builder()
  .url("https://modelslab.com/api/v1/enterprise/load_model_v2")
  .method("POST", body)
  .addHeader("Content-Type", "application/json")
  .build();
Response response = client.newCall(request).execute();

Load a Huggingface Model

Body Raw

{
  "key": "enterprise_api_key",
  "url": "wavymulder/Analog-Diffusion",
  "model_id": "analog-diffusion",
  "model_type": "huggingface",
  "from_safetensors": "no",
  "webhook": "https://modelslab.com",
  "revision": "fp32",
  "upcast_attention": "no"
}

Request: Load a Huggingface Model

JS

var myHeaders = new Headers();
myHeaders.append("Content-Type", "application/json");

var raw = JSON.stringify({
  "key": "enterprise_api_key",
  "url": "wavymulder/Analog-Diffusion",
  "model_id": "analog-diffusion",
  "model_type": "huggingface",
  "from_safetensors": "no",
  "webhook": "https://modelslab.com",
  "revision": "fp32",
  "upcast_attention": "no"
});

var requestOptions = {
  method: 'POST',
  headers: myHeaders,
  body: raw,
  redirect: 'follow'
};

model_reload("https://modelslab.com/api/v1/enterprise/load_model_v2", requestOptions)
  .then(response => response.text())
  .then(result => console.log(result))
  .catch(error => console.log('error', error));

PHP

<?php

$payload = [
  "key" => "enterprise_api_key", 
  "url" => "wavymulder/Analog-Diffusion", 
  "model_id" => "analog-diffusion", 
  "model_type" => "huggingface", 
  "from_safetensors": "no",
  "webhook" => "https://modelslab.com", 
  "revision" => "fp32", 
  "upcast_attention" => "no" 
];

$curl = curl_init();

curl_setopt_array($curl, array(
  CURLOPT_URL => 'https://modelslab.com/api/v1/enterprise/load_model_v2',
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => '',
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 0,
  CURLOPT_FOLLOWLOCATION => true,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => 'POST',
  CURLOPT_POSTFIELDS =>  json_encode($payload),
  CURLOPT_HTTPHEADER => array(
    'Content-Type: application/json'
  ),
));

$response = curl_exec($curl);

curl_close($curl);
echo $response;

NODE

var request = require('request');
var options = {
  'method': 'POST',
  'url': 'https://modelslab.com/api/v1/enterprise/load_model_v2',
  'headers': {
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    "key": "enterprise_api_key",
    "url": "wavymulder/Analog-Diffusion",
    "model_id": "analog-diffusion",
    "model_type": "huggingface",
    "from_safetensors": "no",
    "webhook": "https://modelslab.com",
    "revision": "fp32",
    "upcast_attention": "no"
  })
};

request(options, function (error, response) {
  if (error) throw new Error(error);
  console.log(response.body);
});

PYTHON

import requests
import json

url = "https://modelslab.com/api/v1/enterprise/load_model_v2"

payload = json.dumps({
  "key": "enterprise_api_key",
  "url": "wavymulder/Analog-Diffusion",
  "model_id": "analog-diffusion",
  "model_type": "huggingface",
  "from_safetensors": "no",
  "webhook": "https://modelslab.com",
  "revision": "fp32",
  "upcast_attention": "no"
})

headers = {
  'Content-Type': 'application/json'
}

response = requests.request("POST", url, headers=headers, data=payload)

print(response.text)

JAVA

OkHttpClient client = new OkHttpClient().newBuilder()
  .build();
MediaType mediaType = MediaType.parse("application/json");
RequestBody body = RequestBody.create(mediaType, "{\n    \"key\": \"enterprise_api_key\",\n    \"url\": \"wavymulder/Analog-Diffusion\",\n    \"model_id\": \"analog-diffusion\",\n    \"model_type\": \"huggingface\",\n    \"webhook\": \"https://modelslab.com\",\n    \"revision\": \"fp32\",\n    \"upcast_attention\": \"no\"\n}");
Request request = new Request.Builder()
  .url("https://modelslab.com/api/v1/enterprise/load_model_v2")
  .method("POST", body)
  .addHeader("Content-Type", "application/json")
  .build();
Response response = client.newCall(request).execute();

Request Body: Load a ControlNet Model

Body Raw

{
  "key": "enterprise_api_key",
  "url": "lllyasviel/control_v11p_sd15_canny",
  "model_id": "canny",
  "model_type": "controlnet",
  "webhook": "https://modelslab.com",
  "revision": "fp32",
  "upcast_attention": "no"
}

Request: Load a ControlNet Model

JS

var myHeaders = new Headers();
myHeaders.append("Content-Type", "application/json");

var raw = JSON.stringify({
  "key": "enterprise_api_key",
  "url": "lllyasviel/control_v11p_sd15_canny",
  "model_id": "canny",
  "model_type": "controlnet",
  "webhook": "https://modelslab.com",
  "revision": "fp32",
  "upcast_attention": "no"
});

var requestOptions = {
  method: 'POST',
  headers: myHeaders,
  body: raw,
  redirect: 'follow'
};

model_reload("https://modelslab.com/api/v1/enterprise/load_model_v2", requestOptions)
  .then(response => response.text())
  .then(result => console.log(result))
  .catch(error => console.log('error', error));

PHP

<?php

$payload = [
  "key" => "enterprise_api_key", 
  "url" => "lllyasviel/control_v11p_sd15_canny", 
  "model_id" => "hed", 
  "model_type" => "controlnet", 
  "webhook" => "https://modelslab.com", 
  "revision" => "fp32", 
  "upcast_attention" => "no"
];

$curl = curl_init();

curl_setopt_array($curl, array(
  CURLOPT_URL => 'https://modelslab.com/api/v1/enterprise/load_model_v2',
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => '',
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 0,
  CURLOPT_FOLLOWLOCATION => true,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => 'POST',
  CURLOPT_POSTFIELDS =>  json_encode($payload),
  CURLOPT_HTTPHEADER => array(
    'Content-Type: application/json'
  ),
));

$response = curl_exec($curl);

curl_close($curl);
echo $response;

NODE

var request = require('request');
var options = {
  'method': 'POST',
  'url': 'https://modelslab.com/api/v1/enterprise/load_model_v2',
  'headers': {
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    "key": "enterprise_api_key",
    "url": "lllyasviel/control_v11p_sd15_canny",
    "model_id": "canny",
    "model_type": "controlnet",
    "webhook": "https://modelslab.com",
    "revision": "fp32",
    "upcast_attention": "no"
  })
};

request(options, function (error, response) {
  if (error) throw new Error(error);
  console.log(response.body);
});

PYTHON

import requests
import json

url = "https://modelslab.com/api/v1/enterprise/load_model_v2"

payload = json.dumps({
  "key": "enterprise_api_key",
  "url": "lllyasviel/control_v11p_sd15_canny",
  "model_id": "canny",
  "model_type": "controlnet",
  "webhook": "https://modelslab.com",
  "revision": "fp32",
  "upcast_attention": "no"
})

headers = {
  'Content-Type': 'application/json'
}

response = requests.request("POST", url, headers=headers, data=payload)

print(response.text)

JAVA

OkHttpClient client = new OkHttpClient().newBuilder()
  .build();
MediaType mediaType = MediaType.parse("application/json");
RequestBody body = RequestBody.create(mediaType, "{\n    \"key\": \"enterprise_api_key\",\n    \"url\": \"lllyasviel/control_v11p_sd15_canny\",\n    \"model_id\": \"hed\",\n    \"model_type\": \"controlnet\",\n    \"webhook\": \"https://modelslab.com\",\n    \"revision\": \"fp32\",\n    \"upcast_attention\": \"no\"\n}");
Request request = new Request.Builder()
  .url("https://modelslab.com/api/v1/enterprise/load_model_v2")
  .method("POST", body)
  .addHeader("Content-Type", "application/json")
  .build();
Response response = client.newCall(request).execute();

Response

{
  "message": "model load started",
  "status": "success"
}