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:
- 4c84aa5ce539306f2d3fb1fa16618e8bc26cb201650239cf67b61dbb51f90547
- Size of remote file:
- 1.19 MB
- SHA256:
- 05635fdb7e5449ee24fb0f7e85e23e9ee5a347fc7bf3dc66ae013bd79248bbcb
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