Image-to-Video
Diffusers
Safetensors
English
Chinese
WanImageToVideoPipeline
wan
wan2.1
video-generation
fp16
Instructions to use wavespeed/Wan2.1-I2V-14B-720P-Diffusers-fp16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wavespeed/Wan2.1-I2V-14B-720P-Diffusers-fp16 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("wavespeed/Wan2.1-I2V-14B-720P-Diffusers-fp16", 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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dfa4bb570c8158924cd61581633ac9575ac01b1f5ded7fb6eb870146dacddf32
- Size of remote file:
- 1.26 GB
- SHA256:
- 887861ce8703ff40c6377d91b494cf92c91f23b8337547a1f1226562e092ff27
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