Instructions to use kukuhtw/myflux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kukuhtw/myflux 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("kukuhtw/myflux") prompt = "kukuhtw" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Add generated example
#9
by kukuhtw - opened
Generated example for model kukuhtw/myflux.
Prompt: Kukuh TW, Man a man taking a selfie surrounded by dozens of racks filled with the latest Nvidia GPUs. The GPUs are neatly organized on metal racks, showcasing advanced hardware technology with a futuristic and high-tech environment. The man is smiling, appearing proud and excited about the setup. The room is well-lit, with the glow of LED lights from the GPUs creating a modern and professional atmosphere.