Instructions to use NO8D/ExpressionControl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use NO8D/ExpressionControl 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.2-klein-9B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("NO8D/ExpressionControl") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/ComfyUI_00876_.png
text: '-'
base_model: black-forest-labs/FLUX.2-klein-9B
instance_prompt: null
license: other
license_name: flux-1-dev-non-commercial-license
license_link: LICENSE
Expression Control

- Prompt
- -
Model description
Klein does not have LoRAs like the PixelSmile for QIE2511, so I decided to train a set myself! like the QIE2511 version, this collection allows for fine‑grained and linear control over facial expressions while maintaining high character consistency
Download model
Download them in the Files & versions tab.