Instructions to use molinamarc/syntheva with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use molinamarc/syntheva with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("molinamarc/syntheva", 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:
- 6b7a1bda52defe9e2e460a3f1d506cf3e4421410fd3263e9204df0e4133b10a3
- Size of remote file:
- 95.7 MB
- SHA256:
- 24ccda0d9df78cdc996efd2a9e5600350589a63d690025b3ba5d01ba4cfa0b8e
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