Instructions to use kylix98/actionhug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kylix98/actionhug with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wavespeed/stable-diffusion-xl-base-1.0-fp16", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("kylix98/actionhug") prompt = "actionhug, natural affectionate motion, smooth interaction between two characters, realistic body contact, no sharp transitions." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
ActionHug – LoRA for Natural Affection Motion (WAN 2.2 / I2V Compatible)

- Prompt
- actionhug, natural affectionate motion, smooth interaction between two characters, realistic body contact, no sharp transitions.
Model description
ActionHug is a motion-focused LoRA designed for WAN 2.2 and I2V pipelines, adding a smooth, natural “approach and back-hug” action to any character without changing their identity or body proportions. Trained exclusively on AI-generated clips, this LoRA generalizes well across different scenes, outfits, and poses.
Trigger words
You should use actionhug to trigger the image generation.
Download model
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Model tree for kylix98/actionhug
Base model
stabilityai/stable-diffusion-xl-base-1.0