Instructions to use Keltezaa/KayaS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Keltezaa/KayaS 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("Keltezaa/KayaS") prompt = "photorealistic high quality photo of KayaS" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
KayaS

- Prompt
- photorealistic high quality photo of KayaS
Trigger words
You should use KayaS to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
- Downloads last month
- 24
Model tree for Keltezaa/KayaS
Base model
black-forest-labs/FLUX.1-dev