Diffusers How to use anthienlong/elitebabes 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("anthienlong/elitebabes")
prompt = "Create an ultra-high-detailed, super-realistic image of a 16-year-old girl posing seductively on a worn, wooden dock overlooking a serene lake at sunset. Her skin should have a luminous sheen to it, with fine lines and pores that catch the golden light. She has long, golden blonde hair cascading down her back in loose waves, framing her face with stray strands. Her eyes sparkle bright blue, hinting at mischief. She wears a tight-fitting sports bra displaying the \"Jesse\" on the front, made of translucent fabric that showcases the outline of her nipples and skin texture beneath. The bra is stretched to its limits by her firm H-cup breasts. Underneath, she wears deep purple yoga pants with a subtle sheen, pulled tightly over her athletic build. Her legs are long and lean, with toned muscles visible beneath her skin. Her feet are bare, with strategically-placed scratches or scars on her toes adding to her charm. In one hand, she holds up a small, half-empty water bottle with the text \"Jesses Zaad\" on the bottle in bold letters. The bottle is adorned with a few drops of milk that have escaped its confines, trickling down her chin and onto her lips. A few droplets of milk cling to the corners of her mouth, glistening in the fading light. Her lips are slightly parted, as if she is about to take another sip from the bottle. The expression on her face is one of languid pleasure, with a hint of playfulness in her eyes. The dock is weathered and worn, with wooden planks creaking in the gentle breeze. The lake sparkles in the fading light, reflecting the colors of the sky. A few scattered leaves rustle in the wind, adding to the serene atmosphere."
image = pipe(prompt).images[0] 
