Instructions to use B4100/ridingd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use B4100/ridingd with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TheRaf7/ultra-real-wan2.2", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("B4100/ridingd") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
File size: 769 Bytes
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tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: >-
images/Firefly_gpt-image_Full body shot, young woman age 21, very pale
cool skin — mixed Korean and Norwegian, 482179.png
text: '-'
base_model: TheRaf7/ultra-real-wan2.2
instance_prompt: null
---
# ridingdld
<Gallery />
## Model description
dldoridng, the video start with a woman, the screen quickly goes dark and then lights up again to show a vagina close-up of the same woman riding a plastic dildo in the same place,the toy is in the woman's vagina. she is leaning backwards as she bounces up and down aggressively. Her face is visible.
## Download model
[Download](/B4100/ridingd/tree/main) them in the Files & versions tab.
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