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:
- 550d733fa1e69b7e190da6b3c0cdcd65b5a1f599f2dadea26fd6b8f50e6ccd61
- Size of remote file:
- 4.27 GB
- SHA256:
- 18fa1fc01ed06a137a94a61a81b947ddba4f5fbf26b84514cd3ac303390f30b7
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