Instructions to use biali/stable-diffusion-2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use biali/stable-diffusion-2-base with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("biali/stable-diffusion-2-base", 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 biali/stable-diffusion-2-base: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/biali/stable-diffusion-2-base/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://biali/stable-diffusion-2-base/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/biali/stable-diffusion-2-base/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- dfaf4e2e31bf1af677e1e31a159ba50b78737902ca2ab5729ccdd15a11e69200
- Size of remote file:
- 335 MB
- SHA256:
- a4302e1efa25f3a47ceb7536bc335715ad9d1f203e90c2d25507600d74006e89
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