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

- Xet hash:
- c7f7fd0a509e614a78f638ecf04d2d5dca621ec92f4870129af1d88f55b0453c
- Size of remote file:
- 109 kB
- SHA256:
- e01b56c2a04dd322ff6e942c66f5f0e5a83fa44dff41ca25d940b78339122e79
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