Instructions to use Shakker-Labs/AWPortrait-FL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Shakker-Labs/AWPortrait-FL 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/AWPortrait-FL", 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
- Draw Things
- DiffusionBee
Best options for training and inference
#16
by oddball516 - opened
I have multiple flux.1-dev options,
- the official one
- the dev2pro one
- awportrait finetune
I can pick two different modules for training and inferences. What's the best practice for portraits?