Instructions to use jimmycarter/auraflow-4.8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jimmycarter/auraflow-4.8b with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jimmycarter/auraflow-4.8b", torch_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
What is this
This is AuraFlow pruned to 18 layers from 36 layers, by excising the middle 18 layers. It will make mainly corrupt images until you finetune it for a few thousand steps, after which it should look good.
Usage
pipe = AuraFlowPipeline.from_pretrained("fal/AuraFlow")
del pipe.transformer
transformer = AuraFlowTransformer2DModel.from_pretrained(
"jimmycarter/auraflow-4.8b")
pipe.transformer = transformer
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