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 unet/diffusion_pytorch_model.fp16.bin from biali/stable-diffusion-2-base: direct link, hf CLI and curl.
- Browser
- Download file 1.73 GB
-
https://huggingface.co/biali/stable-diffusion-2-base/resolve/main/unet/diffusion_pytorch_model.fp16.bin
- Command line
-
hf download hf://biali/stable-diffusion-2-base/unet/diffusion_pytorch_model.fp16.bin
-
curl -L -o diffusion_pytorch_model.fp16.bin https://huggingface.co/biali/stable-diffusion-2-base/resolve/main/unet/diffusion_pytorch_model.fp16.bin
1.73 GB
- Xet hash:
- be5264bf67622b51ddbf3dc179ba69aed83ddb53781d6df7160aca54b2300d0c
- Size of remote file:
- 1.73 GB
- SHA256:
- e91ba7ce0800c9cac1086d81f6c247e8c1a06405f63c0f2711f8597a452437dc
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