Instructions to use DeepBeepMeep/Wan2.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DeepBeepMeep/Wan2.2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DeepBeepMeep/Wan2.2", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Diffusion Single File
How to use DeepBeepMeep/Wan2.2 with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 868cd14a6da570c6c394e1b41570a1a1163c895c0a0d0a70a157919458c4573b
- Size of remote file:
- 69.2 MB
- SHA256:
- 4e142db1195bf3f9934711f33677e28932f3206885126850349d621b03f9f01a
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