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 text_encoder/pytorch_model.bin from stablediffusionapi/kisaragimix: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/stablediffusionapi/kisaragimix/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://stablediffusionapi/kisaragimix/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/stablediffusionapi/kisaragimix/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 9f7f4fd046544b279e971fcd8ca1466e9e10f68d4c5ac1df682cee93f838aec2
- Size of remote file:
- 246 MB
- SHA256:
- b1d1ef44f57ec96bf63a8df6b6f2cc7a2d9aad3b65fe99a9a4afdeb00a53904b
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