Instructions to use iamkaikai/amazing-logos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use iamkaikai/amazing-logos with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("iamkaikai/amazing-logos", 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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- e9c11da3b9e9fed371773da11a82c012d1bb482cfcd151a7ab9ce9fa8fb83974
- Size of remote file:
- 14.7 kB
- SHA256:
- 38ce9edafa4dd1894a12948caf847e5058164d56c6dfd569953e4b3c4ddab2a8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.