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
Download vae/diffusion_pytorch_model.bin from Metal079/SonicDiffusionV2: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/Metal079/SonicDiffusionV2/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Metal079/SonicDiffusionV2/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Metal079/SonicDiffusionV2/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- d4bafb3ebb93484da00cd3a831c2489d951c1a7fd48f93194488f7e2f2749582
- Size of remote file:
- 335 MB
- SHA256:
- a5957cb736a8b033eba68c89e74a6d89a3d67090fadb8fe3bb11349953e6d290
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