Instructions to use 2ch/penflux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 2ch/penflux 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("2ch/penflux") prompt = "close-up of thick average length penis, overhanging foreskin, dripping translucent fluid, clear viscous fluid dripping from tip" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
xpenis

- Prompt
- close-up of thick average length penis, overhanging foreskin, dripping translucent fluid, clear viscous fluid dripping from tip

- Prompt
- realistic, highres, outdoors, medieval village, overcast sky, photo of young rugged medieval men with skimpy (loose open shirt:1.5) and (large erect penis:1.3) out of torn medieval style pants, beard, testicles, lying on back, spread legs, masturbating, fat belly, cute, blond
Model description
https://civitai.com/models/961155
Trigger words
You should use uncut penis to trigger the image generation.
You should use flaccid penis to trigger the image generation.
You should use overhanging foreskin to trigger the image generation.
You should use dripping translucent fluid to trigger the image generation.
You should use clear viscous fluid dripping from tip to trigger the image generation.
Download model
Weights for this model are available in PyTorch format.
Download them in the Files & versions tab.
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Model tree for 2ch/penflux
Base model
black-forest-labs/FLUX.1-dev