Instructions to use Jonjew/StaceDash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jonjew/StaceDash 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/StaceDash") prompt = "<lora:stac3yd3sh:1.3>extreme close up, double exposure, beautiful light complexion, 19 years old biracial female in the rain, detailed raindrops running down her face, wet hair, wet clothes stuck to her complete body and legs, super detailed photography, Play of light in the sun rain, downpour, ((a drop of water falling from a height onto the surface of the water)), splashes, luminism, intricate, 4k concept art volumetric light, unrealistic engine, global illumination, detailed environment, full body" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Ctrl+K