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("zenlm/zen-video-i2v", dtype=torch.bfloat16, device_map="cuda")
pipe.to("cuda")
prompt = "A man with short gray hair plays a red electric guitar."
image = load_image(
"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png"
)
output = pipe(image=image, prompt=prompt).frames[0]
export_to_video(output, "output.mp4")zen-video-i2v
Image-to-video generation.
Repackaged from Wan-AI/Wan2.2-I2V-A14B (apache-2.0, Alibaba Wan). Not trained from scratch — a permissively-licensed redistribution for the OSS-clean Zen model line.
License
apache-2.0. Upstream: Wan-AI/Wan2.2-I2V-A14B by Alibaba Wan. Upstream LICENSE/NOTICE retained in-repo.
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