Instructions to use Ching2602/rimming with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ching2602/rimming with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.2-I2V-A14B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Ching2602/rimming") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from Ching2602/rimming: direct link, hf CLI and curl.
- Browser
- Download file 426 Bytes
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https://huggingface.co/Ching2602/rimming/resolve/main/README.md
- Command line
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hf download hf://Ching2602/rimming/README.md
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curl -L -o README.md https://huggingface.co/Ching2602/rimming/resolve/main/README.md
426 Bytes
| tags: | |
| - text-to-image | |
| - lora | |
| - diffusers | |
| - template:diffusion-lora | |
| widget: | |
| - output: | |
| url: images/368ac433-73fc-45be-86a5-bb42dbf4700c.png | |
| text: '-' | |
| base_model: Wan-AI/Wan2.2-I2V-A14B | |
| instance_prompt: null | |
| # rimming | |
| <Gallery /> | |
| ## Model description | |
| A woman performing rimming on a man, licking his anus. | |
| ## Download model | |
| [Download](/profpeng/rimming/tree/main) them in the Files & versions tab. | |