Instructions to use Muapi/lum-urusei-yatsura with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/lum-urusei-yatsura with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/lum-urusei-yatsura") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Lum (γ©γ ) - Urusei Yatsura (γγζγγ€γ)
Base model: Flux.1 D
Trained words: lum, long hair, bangs, blue hair, orange eyes, horns, pointy ears, aqua hair, oni horns, eyeshadow,, navel, cleavage, swimsuit, bikini, strapless, animal print, yellow bikini, tiger print, strapless bikini,, shirt, long sleeves, school uniform, serafuku, sailor collar, neckerchief, yellow neckerchief, shirt, blue shirt, blue sailor collar, blue skirt,
π§ Usage (Python)
π Get your MUAPI key from muapi.ai/access-keys
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality, 1girl, looking at viewer",
"model_id": [{"model": "civitai:650606@727900", "weight": 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/lum-urusei-yatsura
Base model
black-forest-labs/FLUX.1-dev