Instructions to use wxcvbnw/gitlatt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wxcvbnw/gitlatt with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wxcvbnw/gitlatt", 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:
- fec43e1925ad0fec9180a03613d31b20942f46688cda176ed17de49e84fd2385
- Size of remote file:
- 681 MB
- SHA256:
- c9760ce2ade0a1e4267dd365173b6a42722837c996f6980cc68db77bde71a953
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