Instructions to use BIGJUTT/Wan2.2-I2V-A14B-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BIGJUTT/Wan2.2-I2V-A14B-Diffusers 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("BIGJUTT/Wan2.2-I2V-A14B-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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49e18c6e461254ed002e698e5d8be3557e3e3f69733f6eb9b410370981d7b82a
- Size of remote file:
- 16.8 MB
- SHA256:
- 20a46ac256746594ed7e1e3ef733b83fbc5a6f0922aa7480eda961743de080ef
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