Instructions to use rrustom/stable-architecture-diffusers-ema with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rrustom/stable-architecture-diffusers-ema with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rrustom/stable-architecture-diffusers-ema", 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 rrustom/stable-architecture-diffusers-ema: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/rrustom/stable-architecture-diffusers-ema/resolve/refs%2Fpr%2F3/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://rrustom/stable-architecture-diffusers-ema@refs/pr/3/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/rrustom/stable-architecture-diffusers-ema/resolve/refs%2Fpr%2F3/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 30c7d7bb7e84f846cee9ec1c94fad12d9aed59c953a86a1e2656088b4808f6dd
- Size of remote file:
- 3.44 GB
- SHA256:
- b27bc122276b9a59d059fae07bd7b9cd030fac3ddef33bf79a9a3e284b9b093b
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