Instructions to use BoneAppleT/KyleTOK with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BoneAppleT/KyleTOK 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("BoneAppleT/KyleTOK") prompt = "Eyeball" 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:
- text: Eyeball
output:
url: images/1000018064.jpg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: KyleTOK
KyleTOK

- Prompt
- Eyeball
Trigger words
You should use KyleTOK to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.