---
license: creativeml-openrail-m
tags:
  - modelslab.com
  - stable-diffusion-api
  - text-to-image
  - ultra-realistic
pinned: true
---

# ColoringBook API Inference

![generated from modelslab.com](https://pub-3626123a908346a7a8be8d9295f44e26.r2.dev/generations/18433554451721361966.png)
## Get API Key

Get API key from [ModelsLab API](http://modelslab.com), No Payment needed. 

Replace Key in below code, change **model_id**  to "coloringbook"

Coding in PHP/Node/Java etc? Have a look at docs for more code examples: [View docs](https://docs.modelslab.com)

Try model for free: [Generate Images](https://modelslab.com/models/coloringbook)

Model link: [View model](https://modelslab.com/models/coloringbook)

View all models: [View Models](https://modelslab.com/models)

    import requests  
    import json  
      
    url =  "https://modelslab.com/api/v6/images/text2img"  
      
    payload = json.dumps({  
    "key":  "your_api_key",  
    "model_id":  "coloringbook",  
    "prompt":  "ultra realistic close up portrait ((beautiful pale cyberpunk female with heavy black eyeliner)), blue eyes, shaved side haircut, hyper detail, cinematic lighting, magic neon, dark red city, Canon EOS R3, nikon, f/1.4, ISO 200, 1/160s, 8K, RAW, unedited, symmetrical balance, in-frame, 8K",  
    "negative_prompt":  "painting, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, deformed, ugly, blurry, bad anatomy, bad proportions, extra limbs, cloned face, skinny, glitchy, double torso, extra arms, extra hands, mangled fingers, missing lips, ugly face, distorted face, extra legs, anime",  
    "width":  "512",  
    "height":  "512",  
    "samples":  "1",  
    "num_inference_steps":  "30",  
    "safety_checker":  "no",  
    "enhance_prompt":  "yes",  
    "seed":  None,  
    "guidance_scale":  7.5,  
    "multi_lingual":  "no",  
    "panorama":  "no",  
    "self_attention":  "no",  
    "upscale":  "no",  
    "embeddings":  "embeddings_model_id",  
    "lora":  "lora_model_id",  
    "webhook":  None,  
    "track_id":  None  
    })  
      
    headers =  {  
    'Content-Type':  'application/json'  
    }  
      
    response = requests.request("POST", url, headers=headers, data=payload)  
      
    print(response.text)

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