Instructions to use X-HighVoltage-X/Flux-Kontext-Makeup-remover with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use X-HighVoltage-X/Flux-Kontext-Makeup-remover 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-Kontext-dev", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("X-HighVoltage-X/Flux-Kontext-Makeup-remover") prompt = "-" image = pipe(prompt).images[0] - Inference
- 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_00001_.jpeg
text: '-'
- output:
url: images/ComfyUI_00032_.jpeg
text: '-'
- output:
url: images/ComfyUI_00030_.jpeg
text: '-'
- output:
url: images/ComfyUI_00040_.jpeg
text: '-'
- output:
url: images/ComfyUI_00038_.jpeg
text: '-'
- output:
url: images/ComfyUI_00024_.jpeg
text: '-'
- output:
url: images/ComfyUI_00004_.jpeg
text: '-'
- output:
url: images/ComfyUI_00026_.jpeg
text: '-'
- output:
url: images/ComfyUI_00005_.jpeg
text: '-'
base_model: black-forest-labs/FLUX.1-Kontext-dev
instance_prompt: Remove makeup of this person
Flux Kontext Makeup remover

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Model description
This model is a Flux Kontext LoRA trained with the AI-toolkit.
It was trained on 70 image pairs, with around 80% of them featuring Asian subjects. However, since Kontext LoRA learns concepts rather than specific faces, it works well with various ethnicities.
I recommend using a LoRA strength of 1 for best results.
Trigger words
You should use Remove makeup of this person to trigger the image generation.
Download model
Download them in the Files & versions tab.