Instructions to use willseijits/wan2.2-5B-hhpenis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use willseijits/wan2.2-5B-hhpenis 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/Wan2.2-TI2V-5B-Diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("willseijits/wan2.2-5B-hhpenis") prompt = "A man with short gray hair plays a red electric guitar." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Wan2.2
How to use willseijits/wan2.2-5B-hhpenis with Wan2.2:
# 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
- Local Apps Settings
- Draw Things
- Xet hash:
- 09c2a2b09f657cacbe7391ea619e41fc60b9e8be0f6e5f4ec116e14c2430801f
- Size of remote file:
- 16.8 MB
- SHA256:
- e87c960c36d5fbf4e7e76c2469b7eab877be7f8c5992efbf97e44d3123cc6521
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