Instructions to use punzel/wan_emma_watson with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use punzel/wan_emma_watson 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_emma_watson") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Emma Watson

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Model description
Wan 2.2, trained on 18 images of Emma Watson 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: wanemma
helpers: young woman with long wavy brown hair styled with soft curls, brown 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_emma_watson
Base model
Wan-AI/Wan2.2-T2V-A14B