Image-to-Video
Diffusers
Safetensors
Wan2.2
WanImageToVideoDmdPipeline
diffusion
video-generation
turbodiffusion
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("IPostYellow/TurboWan2.2-I2V-A14B-INT8-Diffusers", 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")convert TurboWan2.2-I2V-A14B-720P quant (https://modelscope.cn/models/TurboDiffusion/TurboWan2.2-I2V-A14B-720P/) to TurboWan2.2-I2V-A14B-INT8-Diffusers
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