Instructions to use Gman/diffusers-training-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Gman/diffusers-training-demo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Gman/diffusers-training-demo", 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:
- dd8c94c7b98acbc39c5e84c42c51d5644d43a2a0fa8eb1437e6efd50dd2d6414
- Size of remote file:
- 74.2 MB
- SHA256:
- b441f4c774c0015073b1bae93c6835083dc0ac47c6ef2eb725e681afb97a689f
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