Instructions to use Muapi/cum-pool-concept with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/cum-pool-concept with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OnomaAIResearch/Illustrious-xl-early-release-v0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/cum-pool-concept") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
license: openrail++
library_name: diffusers
base_model: OnomaAIResearch/Illustrious-xl-early-release-v0
tags:
- lora
- text-to-image
- stable-diffusion-xl
- illustrious
- illustrious
pipeline_tag: text-to-image
Cum Pool - Concept
Base model: Illustrious Trained words: lora:cumpool-v2-illustriousxl-lora-nochekaiser:1, cum pool, blush, 2boys, nipples, hetero, sweat, completely nude, uncensored, lying, penis, pussy, solo focus, spread legs, cum, on back, cum in pussy, oral, fellatio, group sex, after sex, cumdrip, spread pussy, threesome, after vaginal, pov, pov hands,
🧠 Usage (Python)
🔑 Get your MUAPI key from muapi.ai/access-keys
import requests, os
url = "https://api.muapi.ai/api/v1/sdxl-lora-image"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality",
"lora_model": "cum-pool-concept",
"lora_strength": 1.0,
"width": 1024,
"height": 1024,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
