Instructions to use Metal079/SonicDiffusionV2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Metal079/SonicDiffusionV2 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/SonicDiffusionV2", 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
- Draw Things
- DiffusionBee
- Xet hash:
- d4bafb3ebb93484da00cd3a831c2489d951c1a7fd48f93194488f7e2f2749582
- Size of remote file:
- 335 MB
- SHA256:
- a5957cb736a8b033eba68c89e74a6d89a3d67090fadb8fe3bb11349953e6d290
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