Instructions to use stablediffusionapi/architectureurbansdlifech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/architectureurbansdlifech 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/architectureurbansdlifech", 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 stablediffusionapi/architectureurbansdlifech: direct link, hf CLI and curl.
- Browser
- Download file 1.72 GB
-
https://huggingface.co/stablediffusionapi/architectureurbansdlifech/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://stablediffusionapi/architectureurbansdlifech/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/stablediffusionapi/architectureurbansdlifech/resolve/main/unet/diffusion_pytorch_model.bin
1.72 GB
- Xet hash:
- 0433a657099da5be3c5c6949f4fc87179c5d5451cf6286ecfa6d2810fe6b1c9e
- Size of remote file:
- 1.72 GB
- SHA256:
- f4504a9cf21af7f5105d75f78dd4d4bb1f4481d098000834dbc6f9d8267d9a52
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