Instructions to use fal/AuraFlow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fal/AuraFlow with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fal/AuraFlow", dtype=torch.bfloat16, device_map="cuda") 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
Is there anyway to run this in colab on t4 gpu?
#27
by bloomedout - opened
I keep trying to run given code but it runs it on ram instead of gpu even after changing runtime type and restarting.
@bloomedout No, this is simply too large to fit in a free colab instance. If you are using a paid instance, you should do pipe.to('cuda')
If you do not want to use a paid instance, use kaggle and it should fit.