Instructions to use Muapi/js_wan_maid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/js_wan_maid 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("wan-ai/Wan2.1-T2V-14B-Diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/js_wan_maid") prompt = "A man with short gray hair plays a red electric guitar." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things

- Xet hash:
- b2faaa46010b375e03a54f28d9004522bd2d2eaf2a9d3267346cf7633142eb7b
- Size of remote file:
- 2.62 MB
- SHA256:
- 2294a436fa1cd5a038e180ef456f8f9a46e2c80922dbfb1404fe353bd5449b1e
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