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:
- 29e5ad9425f4dd932a092c4804d7efbf58bada93d2a9c95e96e00ab00f9818b4
- Size of remote file:
- 1.3 MB
- SHA256:
- 9bd338b0ae2fbc0f3f439c42bf731268696e48148f31a5056efda2b631a8294b
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