Instructions to use snake7gun/Bernini-R-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use snake7gun/Bernini-R-tiny with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("snake7gun/Bernini-R-tiny", 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:
- 7d07ea36d02fd94601d61e778169dbce74716449ce31257c162549bb1a5fc218
- Size of remote file:
- 16.4 MB
- SHA256:
- f936cd1a4f866907d0052ad79a7b18d88d390237addf7682ac8cb366663ad6d3
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