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
GGUF Q8_0 quant
#8
by SporkySporkness - opened
I have been trying to quantize the model to Q8_0, because the base Flux.1 dev Q8_0 works very well, giving nearly identical results to fp16.
However, I have never quantized before, and I did not succeed with AWPortrait-FL. Could you upload a quantized version?
Thank you so much
Let's take a look.
Here is a tutorial how to convert to GGUF verison.
I've tried ComfyUI-GGUF and stable-diffusion.cpp, but am still unable to make it to the end :(
Update: I've finally managed to get it working!
GGUF quants available at https://huggingface.co/SporkySporkness/AWPortrait-FL-GGUF/
Thank you!