Instructions to use dummbatz/lefka with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dummbatz/lefka 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("dummbatz/lefka") prompt = "lefka long, wavy blonde hair and striking greenish-blue eyes wearing a white tank top against a white background. Her face is clearly visible, with her eyes looking directly at the viewer." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
lefka.lora
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- lefka long, wavy blonde hair and striking greenish-blue eyes wearing a white tank top against a white background. Her face is clearly visible, with her eyes looking directly at the viewer.

- Prompt
- lefka long, wavy blonde hair and striking greenish-blue eyes taking a selfie in front of a car, surrounded by plants, trees, buildings, and a clear blue sky.
Trigger words
You should use lefka to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, Forge, etc.
Weights for this model are available in Safetensors format.
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Model tree for dummbatz/lefka
Base model
black-forest-labs/FLUX.1-dev