shoejob
This lora model is uploaded on imagepipeline.io
Model details - A footjob, but with shoes on. Even more niche!
Mostly works with shiny high heels, platforms, and boots. Uses regular footjob images from my footjob lora to help reinforce the footjob concept, so this model is also good at plain old feet. Kept relatively simple for ease of use: All pov, all women, basically all centered.
Understands a tiny bit of posing, such as laying back / sitting up, laying on the floor, from above / sitting on a couch, from below, knees apart / knees together. Also trained for cum on shoes.
It could be improved or expanded in lots of ways, but it's been sitting for a while so I'm going ahead and uploading it for y'all.
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": "11d7b443-3df2-4c53-afb4-89fa02be2b7b",
"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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