imagepipeline/19936-BUKAKAKE-LORA

19936-BUKAKAKE-LORA

This lora model is uploaded on imagepipeline.io

Model details - - "It is rather prone to getting cum on hair, and has a slight bias against facials/cum on faces, so make sure to tune for that in your prompt so it gets proper coverage. It is able to generate excessive cum from a minimal 'bukkake, cum' tag alongside it. A strength of 0.75 is good. -If your model still has a problem with handjobs, penises, etc. and the like, it'll only really make it work marginally better. Given that most models fuck up hands, penises, and other particulates regardless, expect only a marginal improvement. -All v1.0 pics were made with my custom blends. All of these blends have an AOM3 base, so this LoRA should work for you as well if you use AOM3 or a similar model."

How to try this model ?

You can try using it locally or send an API call to test the output quality.

Get your API_KEY from imagepipeline.io. No payment required.

Coding in php javascript node etc ? Checkout our documentation

import requests  
import json  
  
url =  "https://imagepipeline.io/sd/text2image/v1/run"  
  
payload = json.dumps({  
"model_id":  "sd1.5",  
"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":  false,   
"guidance_scale":  7.5,  
"multi_lingual":  "no",  
"embeddings":  "", 
"lora_models": "ed1fa2f8-ec2d-4794-9182-d2242fb538d8", 
"lora_weights":  "0.5" 
})  
  
headers =  {  
'Content-Type':  'application/json',
'API-Key': 'your_api_key'
}  
  
response = requests.request("POST", url, headers=headers, data=payload)  
  
print(response.text)

}

Get more ready to use MODELS like this for SD 1.5 and SDXL :

API Reference

Generate Image

  https://api.imagepipeline.io/sd/text2image/v1

Headers	Type	Description
`API-Key`	`str`	Get your `API_KEY` from imagepipeline.io
`Content-Type`	`str`	application/json - content type of the request body

Parameter	Type	Description
`model_id`	`str`	Your base model, find available lists in models page or upload your own
`prompt`	`str`	Text Prompt. Check our Prompt Guide for tips
`num_inference_steps`	`int [1-50]`	Noise is removed with each step, resulting in a higher-quality image over time. Ideal value 30-50 (without LCM)
`guidance_scale`	`float [1-20]`	Higher guidance scale prioritizes text prompt relevance but sacrifices image quality. Ideal value 7.5-12.5
`lora_models`	`str, array`	Pass the model_id(s) of LoRA models that can be found in models page
`lora_weights`	`str, array`	Strength of the LoRA effect

license: creativeml-openrail-m tags:

imagepipeline
imagepipeline.io
text-to-image
ultra-realistic pinned: false pipeline_tag: text-to-image

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