Instructions to use Jonjew/submergedFlux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jonjew/submergedFlux 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("Jonjew/submergedFlux") prompt = "submergedaf. A hyperrealistic close-up portrait of a young woman partially submerged in water, her freckled face illuminated by cinematic lighting. Her eyes are open, expressive, and reflective, framed by long wet lashes. The water ripples softly around her face, catching golden-orange and teal-blue lighting from above and below. Her skin glistens with droplets, showing fine pores and natural texture. Beneath the surface, intricate water caustics dance across her neck and shoulders, casting shifting light patterns that shimmer like liquid lace. The lighting is soft yet dramatic, blending warm highlights with cool shadows to create an ethereal, dreamlike atmosphere. Her expression is calm, introspective, and vulnerable. The overall tone is emotionally rich, painterly, and intimate. Evoking a suspended moment between breath and thought. " image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Ctrl+K