---
title: analog-diffusion111
canonical_url: "https://www.modelscope.cn/models/stablediffusionapi/analog-diffusion111"
md_url: "https://www.modelscope.cn/models/stablediffusionapi/analog-diffusion111.md"
repository: stablediffusionapi/analog-diffusion111
last_updated: 2025-08-29
license: creativeml-openrail-m
pipeline_tag: text-to-image-synthesis
tasks:
  - text-to-image-synthesis
library_name:
  - lora
  - pytorch
frameworks:
  - pytorch
downloads: 99
stars: 0
tags:
  - stablediffusionapi.com
  - stable-diffusion-api
  - text-to-image
  - ultra-realistic
---

# analog-diffusion111

> analog-diffusion111 - stablediffusionapi 在 ModelScope 开源的模型。Analog Diffusion111 API Inference

stablediffusionapi/analog-diffusion111 是 ModelScope 魔搭社区上的text-to-image-synthesis模型，采用 creativeml-openrail-m 许可。

- **Repository**: stablediffusionapi/analog-diffusion111
- **License**: creativeml-openrail-m
- **Tasks**: text-to-image-synthesis
- **Tags**: stablediffusionapi.com, stable-diffusion-api, text-to-image, ultra-realistic
- **Downloads**: 99
- **Stars**: 0
- **Last updated**: 2025-08-29

Source: https://www.modelscope.cn/models/stablediffusionapi/analog-diffusion111

---

# Analog Diffusion111 API Inference

![generated from modelslab.com](https://assets.modelslab.com/generations/d3d3f607-e8c6-4758-903a-17804fb4002b-0.png)
## Get API Key

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

Replace Key in below code, change **model_id**  to "analog-diffusion111"

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

Try model for free: [Generate Images](https://stablediffusionapi.com/models/analog-diffusion111)

Model link: [View model](https://stablediffusionapi.com/models/analog-diffusion111)

Credits: [View credits](https://civitai.com/?query=Analog%20Diffusion111)

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

    import requests  
    import json  
      
    url =  "https://stablediffusionapi.com/api/v4/dreambooth"  
      
    payload = json.dumps({  
    "key":  "your_api_key",  
    "model_id":  "analog-diffusion111",  
    "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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