Instructions to use Muapi/facial-concept with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/facial-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/facial-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
Facial - Concept
Base model: Illustrious Trained words: lora:facial-v4-illustriousxl-lora-nochekaiser:1, facial, blush, open mouth, 1boy, nipples, collarbone, hetero, nude, uncensored, lying, penis, tongue, solo focus, tongue out, cum, on back, completely nude, ejaculation, masturbation, cum in mouth, male masturbation, excessive cum, cum on hair, cum on face,
🧠 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": "facial-concept",
"lora_strength": 1.0,
"width": 1024,
"height": 1024,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
