Instructions to use Metal079/SonicDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Metal079/SonicDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Metal079/SonicDiffusion", torch_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:
- 96e524f897777d0e9eb935c9e9645eec233d99e50bdc1da300457e831b639f87
- Size of remote file:
- 492 MB
- SHA256:
- 3ed681199f8c13e3b287c44958f5a554cf930177b4ebe9ee13ecd0b4404c4e29
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