Instructions to use aaronsiim/diffusionai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aaronsiim/diffusionai with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("aaronsiim/diffusionai", 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 aaronsiim/diffusionai: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/aaronsiim/diffusionai/resolve/refs%2Fpr%2F2/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://aaronsiim/diffusionai@refs/pr/2/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/aaronsiim/diffusionai/resolve/refs%2Fpr%2F2/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 47a31e24dcd24e953d57bfe253064421b56bca8292f13c76140756fa0d988b6a
- Size of remote file:
- 3.44 GB
- SHA256:
- b02092a9e9180222a3abbb16ed576f2e24736011df15c09c904266d9a95f7dca
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