Instructions to use VHKE/henkeb00ble with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VHKE/henkeb00ble 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("VHKE/henkeb00ble") prompt = "Henkeb00ble placed on a rock --d 45" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Henkeb00ble
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- Henkeb00ble placed on a rock --d 45

- Prompt
- Henkeb00ble in a poster ad --d 45

- Prompt
- Henkeb00ble held by a teen --d 45
Trigger words
You should use Henkeb00ble 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 VHKE/henkeb00ble
Base model
black-forest-labs/FLUX.1-dev