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:
- 09e0d6edbbb0aafe9a95d6502bc3885a010bb39b5971dbd291ef3a075eacb2c2
- Size of remote file:
- 95.7 MB
- SHA256:
- 009d6814d1bc560d4e7b236e170e9b2d5ca6f4b57bd8037f6db05776204415c6
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