Train a Lora Model with Custom Images

Request

Make a POST request to below endpoint and pass the required parameters as a request body.

curl

--request POST 'https://modelslab.com/api/v3/lora_fine_tune' \

For now, you can only train a model on normal lora models and sdxl and get its style.

Training Types

The table below lists all the possible values for the training_type parameter.

Value	Description
men	Train on faces of men.
female	Train on faces of females.
couple	Train on couples of male and female; in images array pass images of couples, instead of images of a single person.
null	Train on object or anything.

Training Status Values

The table below describes all possible training statuses.

Status	Description
deploying_gpu	Deploying GPU
training_started	Training started
training_success	Training completed successfully
trained_model_compressing	Compressing the trained model
trained_model_uploading	Uploading the trained model
trained_model_uploaded	Trained model uploaded
deploying_model	Deploying the trained model
model_ready	The trained model is ready for use

Body

json

{    
    "key":"",    
    "instance_prompt": "photo of ambika0 man",    
    "class_prompt": "photo of a man",    
    "base_model_type": "sdxl",    
    "negative_prompt":" lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry",    
    "images": [    
        "https://raw.githubusercontent.com/pnavitha/sampleImages/master/1.png",    
        "https://raw.githubusercontent.com/pnavitha/sampleImages/master/2.png",    
        "https://raw.githubusercontent.com/pnavitha/sampleImages/master/3.png",    
        "https://raw.githubusercontent.com/pnavitha/sampleImages/master/4.png",    
        "https://raw.githubusercontent.com/pnavitha/sampleImages/master/5.png",    
        "https://raw.githubusercontent.com/pnavitha/sampleImages/master/6.png",    
        "https://raw.githubusercontent.com/pnavitha/sampleImages/master/7.png",    
        "https://raw.githubusercontent.com/pnavitha/sampleImages/master/8.png",    
        "https://raw.githubusercontent.com/pnavitha/sampleImages/master/9.png"  
    ],    
    "seed": "0",    
    "training_type": "men",    
    "max_train_steps": "18",    
    "lora_type":"lora",    
    "webhook": null
}

Webhook

This is an example webhook post call in JSON format.

json

{ 
    "status": "success", 
    "training_status": "deploying_gpu", 
    "logs": "it will take upto 25 minutes", 
    "model_id": "F5jvdzGnYi"
}

Request

JS
PHP
NODE
PYTHON
JAVA

var myHeaders = new Headers();myHeaders.append("Content-Type", "application/json");var raw = JSON.stringify({    "key":"",    "instance_prompt": "photo of ambika0 man",    "class_prompt": "photo of a man",    "base_model_type": "sdxl",    "negative_prompt":" lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry",    "images": [    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/1.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/2.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/3.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/4.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/5.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/6.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/7.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/8.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/9.png"  ],    "seed": "0",    "training_type": "men",    "max_train_steps": "18",    "lora_type":"lora",    "webhook": null});var requestOptions = {  method: 'POST',  headers: myHeaders,  body: raw,  redirect: 'follow'};fetch("https://modelslab.com/api/v3/lora_fine_tune", requestOptions)  .then(response => response.text())  .then(result => console.log(result))  .catch(error => console.log('error', error));

<?php$payload = [  "key" => "",   "instance_prompt" => "photo of ambika0 man",   "class_prompt" => "photo of person",   "base_model_type" => "sdxl",  "negative_prompt" => " lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry",  "images" => [    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/1.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/2.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/3.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/4.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/5.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/6.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/7.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/8.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/9.png"  ],   "seed" => "0",   "training_type" => "men",   "lora_type":"lora",  "max_train_steps" => "18",   "webhook" => "" ];$curl = curl_init();curl_setopt_array($curl, array(  CURLOPT_URL => 'https://modelslab.com/api/v3/lora_fine_tune',  CURLOPT_RETURNTRANSFER => true,  CURLOPT_ENCODING => '',  CURLOPT_MAXREDIRS => 10,  CURLOPT_TIMEOUT => 0,  CURLOPT_FOLLOWLOCATION => true,  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,  CURLOPT_CUSTOMREQUEST => 'POST',  CURLOPT_POSTFIELDS => json_encode($payload),  CURLOPT_HTTPHEADER => array(    'Content-Type: application/json'  ),));$response = curl_exec($curl);curl_close($curl);echo $response;

var request = require('request');var options = {  'method': 'POST',  'url': 'https://modelslab.com/api/v3/lora_fine_tune',  'headers': {    'Content-Type': 'application/json'  },  body: JSON.stringify({    "key":"",    "instance_prompt": "photo of ambika0 man",    "class_prompt": "photo of a man",    "base_model_type": "sdxl",    "negative_prompt":" lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry",    "images": [    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/1.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/2.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/3.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/4.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/5.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/6.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/7.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/8.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/9.png"  ],    "seed": "0",    "training_type": "men",    "max_train_steps": "18",    "lora_type":"lora",    "webhook": null  })};request(options, function (error, response) {  if (error) throw new Error(error);  console.log(response.body);});

import requestsimport jsonurl = "https://modelslab.com/api/v3/lora_fine_tune"payload = json.dumps({    "key":"",    "instance_prompt": "photo of ambika0 man",    "class_prompt": "photo of a man",    "base_model_type": "sdxl",    "negative_prompt":" lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry",    "images": [    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/1.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/2.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/3.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/4.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/5.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/6.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/7.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/8.png",    "https://raw.githubusercontent.com/pnavitha/sampleImages/master/9.png"    ],    "seed": "0",    "training_type": "men",    "max_train_steps": "18",    "lora_type":"lora",    "webhook": "",})headers = {  'Content-Type': 'application/json'}response = requests.request("POST", url, headers=headers, data=payload)print(response.text)

OkHttpClient client = new OkHttpClient().newBuilder()  .build();MediaType mediaType = MediaType.parse("application/json");RequestBody body = RequestBody.create(mediaType, "{\n    \"key\":\"\",\n    \"instance_prompt\": \"photo of ambika0 man\",\n    \"class_prompt\": \"photo of a man\",\n    \"base_model_type\": \"normal\",\n    \"negative_prompt\":\" lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry\",\n    \"images\": [\n    \"https://raw.githubusercontent.com/pnavitha/sampleImages/master/1.png\",\n    \"https://raw.githubusercontent.com/pnavitha/sampleImages/master/2.png\",\n    \"https://raw.githubusercontent.com/pnavitha/sampleImages/master/3.png\",\n    \"https://raw.githubusercontent.com/pnavitha/sampleImages/master/4.png\",\n    \"https://raw.githubusercontent.com/pnavitha/sampleImages/master/5.png\",\n    \"https://raw.githubusercontent.com/pnavitha/sampleImages/master/6.png\",\n    \"https://raw.githubusercontent.com/pnavitha/sampleImages/master/7.png\",\n    \"https://raw.githubusercontent.com/pnavitha/sampleImages/master/8.png\",\n    \"https://raw.githubusercontent.com/pnavitha/sampleImages/master/9.png\"\n  ],\n    \"seed\": \"0\",\n    \"training_type\": \"men\",\n    \"max_train_steps\": \"18\",\n    \"lora_type\":\"lora\",\n    \"webhook\": null\n}");Request request = new Request.Builder()  .url("https://modelslab.com/api/v3/lora_fine_tune")  .method("POST", body)  .addHeader("Content-Type", "application/json")  .build();Response response = client.newCall(request).execute();

Response

{  "status": "success",  "messege": "deploying_gpu",  "data": "it will take upto 30 minutes.",  "training_id": "F5jvdzGnYi"}

Body

application/json

key

string

required

Your API Key used for request authorization

instance_prompt

string

required

Text prompt with how you want to call your trained person/object

Example:

"photo of ambika0 man"

class_prompt

string

required

Classification of the trained person/object

Example:

"photo of a man"

images

string<uri>[]

required

Accessible direct links to images, cropped to 512x512 pixels. A good number is about 7-8 images

Minimum length: 1

training_type

enum<string>

default:men

required

The type of the object you are training on

Available options:

men,

women,

couple,

null

max_train_steps

string

default:18

required

Set at 2 times the number of images (Ni*2); minimum value is 10 and maximum value is 50

Example:

"18"

wandb_key

string

Key to the wandb platform to monitor your training process

base_model_type

enum<string>

default:sdxl

The type of LoRA base model you want to train on

Available options:

normal,

sdxl

negative_prompt

string

default: lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry

Items you don't want in the image

Example:

"lowres, bad anatomy, bad hands, text, error"

lora_type

enum<string>

default:lora

Type of LoRA model

Available options:

lora,

lycoris

seed

string

default:0

Random seed for reproducible results

webhook

string<uri> | null

Set a URL to receive a POST call when training is complete

Response

Training initiated successfully

status

string

Example:

"success"

messege

enum<string>

Current training status

Available options:

deploying_gpu,

training_started,

training_success,

trained_model_compressing,

trained_model_uploading,

trained_model_uploaded,

deploying_model,

model_ready

data

string

Additional information about the training process

training_id

string

Unique identifier for the training job

Using the APIs

Our AI APIs

Train a Lora Model with Custom Images

Request

Training Types

Training Status Values

Body

Webhook

Request

Response

Body

Response

Using the APIs

Our AI APIs

​Request

​Training Types

​Training Status Values

​Body

​Webhook

​Request​

​Response​

Body

Response

Request

Training Types

Training Status Values

Body

Webhook

Request

Response