Instructions to use Muapi/namila-collection-flux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/namila-collection-flux 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/namila-collection-flux") 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
Namila Collection [Flux]
Base model: Flux.1 D Trained words: Fame, wearing a daring outfit consisting of a black leather bikini top and bottom, both featuring bold pink text that reads "FAME" and "BITCH." The top includes a strap that is suspended around her neck and a chain detail, while the bottom has similar chain accent, is wearing a two-piece outfit consisting of a black crop top and matching bikini bottom. Both pieces feature large white lettering spelling "FAME BITCH," with the top also adorned with chains for embellishment.
🧠 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:972440@1160831", "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/namila-collection-flux
Base model
black-forest-labs/FLUX.1-dev