Instructions to use Muapi/assisted-exposure-concept with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/assisted-exposure-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/assisted-exposure-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
Assisted Exposure - Concept
Base model: Illustrious Trained words: lora:assisted-exposure-v4-illustriousxl-lora-nochekaiser:1, assisted exposure, blush, nipples, hetero, solo focus, pulling another's clothes, looking down, surprised, hands up, pov, pov hand, breasts out,, lora:assisted-exposure-v4-illustriousxl-lora-nochekaiser:1, assisted exposure, looking at viewer, blush, open mouth, nipples, upper body, solo focus, pov, clothes pull, breasts out, 1boy, between breasts, shirt pull, clothes between breasts, angry, embarrassed, pov hand, hetero, solo focus, pulling another's clothes,, lora:assisted-exposure-v4-illustriousxl-lora-nochekaiser:1, assisted exposure, blush, open mouth, 1boy, nipples, upper body, hetero, solo focus, breasts out, surprised, lactation, projectile lactation, pov, pov hand, hands up, looking down,, lora:assisted-exposure-v4-illustriousxl-lora-nochekaiser:1, assisted exposure, looking at viewer, blush, open mouth, 1boy, nipples, upper body, hetero, sweat, clothes pull, breasts out, pulling another's clothes, pov, pov hand, clothes between breasts,
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": "assisted-exposure-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/assisted-exposure-concept
Base model
KBlueLeaf/kohaku-xl-beta5