Instructions to use ashllay/stable-diffusion-v1-1-archive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ashllay/stable-diffusion-v1-1-archive with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ashllay/stable-diffusion-v1-1-archive", 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.bin from ashllay/stable-diffusion-v1-1-archive: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/ashllay/stable-diffusion-v1-1-archive/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://ashllay/stable-diffusion-v1-1-archive/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/ashllay/stable-diffusion-v1-1-archive/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 8d0176e4d6cea8e94a42d4f9937072fa5982d2564b03aa2fe5ab739359d0cc90
- Size of remote file:
- 3.44 GB
- SHA256:
- e1b7658d2a2da153182bef9401ed67f719e559e3b4e994019573c101c8864504
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