Instructions to use Siliconic/raven-diffusion-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Siliconic/raven-diffusion-v1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Siliconic/raven-diffusion-v1", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- afbc61c57db5ca089fa39dec38001acb626efd7cd2e8f6bdc3149810b4f08dc6
- Size of remote file:
- 492 MB
- SHA256:
- 72df7235f726ebb65ed243524c599424a30c3fca2688550a9794d1bdf95d96c0
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