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
Rename Wan2_2_Fun_VACE_A14B_HIGH_quanto_fp16_int8.safetensors to Wan2_2_Fun_VACE_A14B_HIGH_quanto_mfp16_int8.safetensors
Browse files
Wan2_2_Fun_VACE_A14B_HIGH_quanto_fp16_int8.safetensors → Wan2_2_Fun_VACE_A14B_HIGH_quanto_mfp16_int8.safetensors
RENAMED
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