Image-to-Image
Diffusers
flux
flux2
klein
pose
openpose
controlnet
refcontrol
img2img
image
editing
lora
Instructions to use thedeoxen/refcontrol-FLUX.2-klein-9B-reference-pose-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use thedeoxen/refcontrol-FLUX.2-klein-9B-reference-pose-lora with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("thedeoxen/refcontrol-FLUX.2-klein-9B-reference-pose-lora") pipe = StableDiffusionControlNetPipeline.from_pretrained( "black-forest-labs/FLUX.2-klein-base-9B", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Did you train this to be used for 1 mega pixel?
#1
by giredo - opened
Resolutions like 2 mega pixels produce weird anatomy problems.
Flux Klein 9B can go to 4 mega pixels easily.
Trying to figure out what is the problem.
What strength of this lora to use and what effects it has?
What generation resolutions x/y you suggest should be best to avoid problems?