Instructions to use hellokn/wakey with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hellokn/wakey 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("hellokn/wakey") prompt = "wakeup, a giant yellow horse lying down in a green landscape while tiny people in equestrian clothing groom its mane. The horse wears a patterned orange scarf. Background features orange skies, pink clouds, and a distant mountain. Foreground has oversized colorful flowers. Flat illustration style, heavy paper grain, vibrant colors, surreal scale." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Wakey
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- wakeup, a giant yellow horse lying down in a green landscape while tiny people in equestrian clothing groom its mane. The horse wears a patterned orange scarf. Background features orange skies, pink clouds, and a distant mountain. Foreground has oversized colorful flowers. Flat illustration style, heavy paper grain, vibrant colors, surreal scale.
Trigger words
You should use wakeup 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 hellokn/wakey
Base model
black-forest-labs/FLUX.1-dev