Instructions to use X-HighVoltage-X/chinfixer-2000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use X-HighVoltage-X/chinfixer-2000 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("X-HighVoltage-X/chinfixer-2000") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Chin Fixer 2000 v3.0

- Prompt
- -
Model description
designed to reduce the cleft chin seen in a lot of flux images also reduce the shine
Trigger words
You should use chin to trigger the image generation.
You should use cleft chin to trigger the image generation.
You should use jawbone to trigger the image generation.
You should use bottom of head to trigger the image generation.
Download model
Download them in the Files & versions tab.
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Model tree for X-HighVoltage-X/chinfixer-2000
Base model
black-forest-labs/FLUX.1-dev