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:
- 79b6d11b568d42200563be97a1738df198623a27cfc0ca39362596831c795d89
- Size of remote file:
- 2.61 GB
- SHA256:
- 02222da33e5f793b5091000402a08c946538cc9c4a6546734c135e789afde12d
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