Instructions to use GraydientPlatformAPI/kisaragi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GraydientPlatformAPI/kisaragi with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("GraydientPlatformAPI/kisaragi", 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.safetensors from GraydientPlatformAPI/kisaragi: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/GraydientPlatformAPI/kisaragi/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://GraydientPlatformAPI/kisaragi/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/GraydientPlatformAPI/kisaragi/resolve/main/vae/diffusion_pytorch_model.safetensors
167 MB
- Xet hash:
- 617a8ad32fa5589f8b1eb75797887a67547925e7157a2b8acb2797713c875686
- Size of remote file:
- 167 MB
- SHA256:
- 3743d303713270a217fce4db812f61907059a9ffe8244cf57b758a2b30fabfbf
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