Instructions to use stablediffusionapi/kisaragimix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/kisaragimix with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/kisaragimix", 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 stablediffusionapi/kisaragimix: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/stablediffusionapi/kisaragimix/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://stablediffusionapi/kisaragimix/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/stablediffusionapi/kisaragimix/resolve/main/vae/diffusion_pytorch_model.bin
167 MB
- Xet hash:
- aed38d07ca0c07d7ee2e235231b73a723aaa44dd2e7998f981068e3cfda1617c
- Size of remote file:
- 167 MB
- SHA256:
- ebbecf27c96958c91a257fd3c800f296213b664747e3fc0b38dd7f9a05ae91b2
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