Instructions to use singelette/fluxkleinZ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use singelette/fluxkleinZ with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wikeeyang/Flux2-Klein-9B-True-V2", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("singelette/fluxkleinZ") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/c81bec17-d217-48c1-aeba-321cd5bdf214.png
text: '-'
base_model: wikeeyang/Flux2-Klein-9B-True-V2
instance_prompt: null
license: bigscience-bloom-rail-1.0
FLUXKLEIN

- Prompt
- -
Download model
Download them in the Files & versions tab.