Instructions to use Wan-AI/Wan2.1-I2V-14B-720P with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wan-AI/Wan2.1-I2V-14B-720P 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/Wan2.1-I2V-14B-720P", 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") - Inference
- Notebooks
- Google Colab
- Kaggle
Wan2.1 Image to Video Support for MacOS MLX
#5
by Ekolawole - opened
When are we getting Wan2.1 Image to Video Support for MacOS MLX. Community please can someone do this miracle? We need full support not CPU only
Good
On GitHub there is a fork that is trying to make it compatible with MPS, but 1 second (16 frames) needs 8 minutes and about 180 GIGs of unified memory. With the 1.3B-model I can create about 3 seconds on M2 Ultra (125 GIGs unified memory). 480p, I think.
What is the GitHub repository link for the MPS version?