Instructions to use s3nh/beksinski-style-stable-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use s3nh/beksinski-style-stable-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("s3nh/beksinski-style-stable-diffusion", 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 s3nh/beksinski-style-stable-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/s3nh/beksinski-style-stable-diffusion/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://s3nh/beksinski-style-stable-diffusion/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/s3nh/beksinski-style-stable-diffusion/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 0a1e1414a525cc94a219eec7df3f144da0def853a310ac62cba5f0f11ed2bbdd
- Size of remote file:
- 492 MB
- SHA256:
- bc272635d0c02e0b7541f691ccfdfe16df0454e1b3ca694ce60c975a048ab078
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