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:
- 3c3065e28167642dedb81d6ab757067133c2910206d1bd638f4c933696ee7bb1
- Size of remote file:
- 662 kB
- SHA256:
- 77f4930c0c9f3d5955b1d75263a905bf41d4ab83a70a75cc3243222cefee5730
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