Instructions to use Muapi/model-1011208 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/model-1011208 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/model-1011208") 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
写实-青春校园
Base model: Flux.1 D Trained words: The Stealing Photographs of Junior High School Female Students in the Classroom,10 million pixel phone shooting,((early teen)), 中间写(服装,姿势,环境) 也可以自己全部写,往平常的手机拍摄效果靠 The picture has soft texture,elegant colors,natural light,obvious light and shadow contrast,light,(increased noise and texture:1.3),and high resolution,
🧠 Usage (Python)
🔑 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:1011208@1133511", "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/model-1011208
Base model
black-forest-labs/FLUX.1-dev