Instructions to use nathanReitinger/MNIST-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nathanReitinger/MNIST-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nathanReitinger/MNIST-diffusion", 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 samples/0005.png from nathanReitinger/MNIST-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 4.81 kB
-
https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0005.png
- Command line
-
hf download hf://nathanReitinger/MNIST-diffusion/samples/0005.png
-
curl -L -o 0005.png https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0005.png
4.81 kB

- Xet hash:
- 13290519cc28aee3fe912034629715900b7b8c3b68ea6577421c87f49941ef94
- Size of remote file:
- 4.81 kB
- SHA256:
- 8062fabcf67b30e0d0d814132d1a1dda3a04ba4f25e7c79f9eca61fa814dfda5
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