Instructions to use Shakker-Labs/AWPortraitCN2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Shakker-Labs/AWPortraitCN2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Shakker-Labs/AWPortraitCN2", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 5261cdc876098fbb81aa3a39a03e031b99d7bebf50c33fef933990db5f78002b
- Size of remote file:
- 1.67 MB
- SHA256:
- c78a685376a61cf0781ee793bbc8543f59c030673533955d818d812e97d33676
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