Instructions to use Remade-AI/kissing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Remade-AI/kissing with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.1-I2V-14B-480P,Wan-AI/Wan2.1-I2V-14B-480P-Diffusers", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Remade-AI/kissing") prompt = "A man and a woman wearing jackets and hats are standing close together in the snowy mountains. The man is standing facing the woman, then they engage in k144ing kissing." input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png") image = pipe(image=input_image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- Xet hash:
- 2c02629eb9555aac5f71c60a637c7d1168e2a8a72a2dfdbf28e121c39c12b69c
- Size of remote file:
- 1.74 MB
- SHA256:
- 560c8f6f372eb65bf3ed43dabaed692874de3689c05696ac22cc34d6f19fb5f0
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