Instructions to use Svngoku/AfricanLifeStyleFluxLora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Svngoku/AfricanLifeStyleFluxLora 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("Svngoku/AfricanLifeStyleFluxLora") prompt = "12k African lifestyle, marketing, lifestyle, happiness" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Add generated example
#12
by Svngoku - opened
Generated example for model Svngoku/AfricanLifeStyleFluxLora.
Prompt: Experimental shooting, in the style of Ohio academia, high detail, close-up of the upper body, smiling tennis player. Aerial shot, black and white sports skirt with navy blue accents, black woman long hair in a ponytail, wearing a visor hat, holding a racket, smiling at the camera, standing on the court.with the style of African lifestyle
Svngoku changed pull request status to merged