Instructions to use Muapi/rainbow-pie with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/rainbow-pie 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/rainbow-pie") 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:
- c161e83c8bafbba67ab7e631e182a4add0d53c368604e7c2826fb736a192c7f3
- Size of remote file:
- 318 kB
- SHA256:
- 63e6d697d5107b2447d6a25e4cc88b2d390648d0cc9036cbce1f675714326ecb
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