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", 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:
- 7f24bdff19fd578c3979ad51aad1f8938350dcde6e7faedfcf64fed4bbdc361d
- Size of remote file:
- 3.44 GB
- SHA256:
- b7d872f95fbf50808751c85ba2383b9d662282fb4fff11a5f6417d6a00234c3b
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