Instructions to use joyfox/Wan2.2-I2V-KungFu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use joyfox/Wan2.2-I2V-KungFu 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/Wan2.2-I2V-A14B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("joyfox/Wan2.2-I2V-KungFu") prompt = "一个小孩双脚直立,双臂灵活张开,时而抬手,然后转身朝向左边,时而踢腿,做着一系列打拳动作,wugong" 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") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- Xet hash:
- 9b630c76943a028324d0db4e85a5b221659df28b2300472e9e92827fa3b3f830
- Size of remote file:
- 1.79 MB
- SHA256:
- 32fbce375bba74f38805bc54da675d4cce6b3d26dd4473c009434d46bef94c26
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