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:
- f9fab15e3ab695225324f0f82fb90690655eb14c1e701a66b25e5131d31a1288
- Size of remote file:
- 1.93 MB
- SHA256:
- 2a2db87985be81b5a8f6a13f6c9724119c6905b0cf888bdf13bd35371e2aaa38
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