Instructions to use punzel/wan_sydney_sweeney with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use punzel/wan_sydney_sweeney with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.2-T2V-A14B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("punzel/wan_sydney_sweeney") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Sydney Sweeney

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Model description
Testing out Wan 2.2, trained on 18 images of Sydney Sweeney for 1800 steps. This includes a high and low model. All images were generated in 30 steps using 15 steps for the high lora and 15 steps for the low lora.
trigger: wansyd
helpers: young woman with long wavy blonde hair, blue eyes, fair skin, and subtle makeup
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for punzel/wan_sydney_sweeney
Base model
Wan-AI/Wan2.2-T2V-A14B