Instructions to use ZhengmingYu/DMAD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ZhengmingYu/DMAD with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MiniMaxAI/MiniMax-H3", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ZhengmingYu/DMAD") prompt = "A man with short gray hair plays a red electric guitar." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Inference
- Notebooks
- Google Colab
- Kaggle
Add the wan2.1 DMAD weights
Browse files
wan2.1/dmad_wan2pt1_14B.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:e8c7cf5e3fd525258aecb6b34c5e5c767a72db732db21d90fd0cd25115df553d
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size 28577348498
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wan2.1/dmad_wan2pt1_1pt3B.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:763249cc7c27f43e64bb21240e840e242c513cdd1c9bcf92b9fe486de579921e
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size 2838249419
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