Instructions to use MIN-Lab/minWM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MIN-Lab/minWM 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("MIN-Lab/minWM", 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
Download Wan21/Action2V/bidirectional/model_v2.pt from MIN-Lab/minWM: direct link, hf CLI and curl.
- Browser
- Download file 5.96 GB
-
https://huggingface.co/MIN-Lab/minWM/resolve/main/Wan21/Action2V/bidirectional/model_v2.pt
- Command line
-
hf download hf://MIN-Lab/minWM/Wan21/Action2V/bidirectional/model_v2.pt
-
curl -L -o model_v2.pt https://huggingface.co/MIN-Lab/minWM/resolve/main/Wan21/Action2V/bidirectional/model_v2.pt
5.96 GB
- Xet hash:
- f033ad6d4de5d732b9f0e7fef1ce800bf9150a51eb80d47370b2416f8ffe0d39
- Size of remote file:
- 5.96 GB
- SHA256:
- 28e65f89661b5e77f58dd1c78457d5f63e471c7768f0ae99a203d08fe6398132
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