Instructions to use fjans/dnb-diffusion-256-ddim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fjans/dnb-diffusion-256-ddim with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fjans/dnb-diffusion-256-ddim", 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
Download unet/diffusion_pytorch_model.bin from fjans/dnb-diffusion-256-ddim: direct link, hf CLI and curl.
- Browser
- Download file 150 MB
-
https://huggingface.co/fjans/dnb-diffusion-256-ddim/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://fjans/dnb-diffusion-256-ddim/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/fjans/dnb-diffusion-256-ddim/resolve/main/unet/diffusion_pytorch_model.bin
150 MB
- Xet hash:
- ef0d75f4a938c137c96c4b3161eb3bf3b4686fa34fadf1fbad9c4f7ef4623827
- Size of remote file:
- 150 MB
- SHA256:
- 9cd157426f37e71076000a43cc23bdc9959aedba720d4bd52168fee738782757
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