Instructions to use Muapi/oppai-challenge-concept with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/oppai-challenge-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/oppai-challenge-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
Oppai Challenge - Concept
Base model: Illustrious Trained words: lora:oppai-challenge-v2-illustriousxl-lora-nochekaiser:1, oppai challenge, oppai challenge (meme), solo focus, looking at viewer, blush, smile, closed mouth, nipples, upper body, outdoors, sweat, one eye closed, japanese clothes, kimono, night, no bra, floral print, obi, index finger raised, finger to mouth, yukata, one breast out, public indecency, exhibitionism, shushing, flashing, public nudity, festival, summer festival,
๐ง Usage (Python)
๐ 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": "oppai-challenge-concept",
"lora_strength": 1.0,
"width": 1024,
"height": 1024,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
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Model tree for Muapi/oppai-challenge-concept
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KBlueLeaf/kohaku-xl-beta5