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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 958182bc1743d3f4009a96b6fbbf3fb5fa2e03da3360a94ce1d0006a2c894c37
- Size of remote file:
- 3.44 GB
- SHA256:
- f5bc3d5b3d988465a4589ce57d4237b99e68f692c84973907d2513950d63be3f
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