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
- Draw Things
- DiffusionBee
- Xet hash:
- 793a8d9916acb839921964e3197b4ddea0e91ecd3b0fe92cf5e8afba2ad39119
- Size of remote file:
- 680 MB
- SHA256:
- fde6d41cf184ed64a942447955cf0204102eeabfa1d220bb1ad542ecee7cbca3
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