Instructions to use Akiyue/awwl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Akiyue/awwl with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Akiyue/awwl", 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

- Xet hash:
- bf572904423496060066102bc6c1f8e731606bd3997c8047feccdf218917816f
- Size of remote file:
- 271 kB
- SHA256:
- afba2d9fbe27bb4d0a9c52aec484a2a32d9f92e2c682de5c10b7272496c59ad5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.