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/0010.png from nathanReitinger/MNIST-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 4.99 kB
-
https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0010.png
- Command line
-
hf download hf://nathanReitinger/MNIST-diffusion/samples/0010.png
-
curl -L -o 0010.png https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0010.png
4.99 kB

- Xet hash:
- 50b17c1c7c9b0f656a3208e872c364bf2f057495da733494401e5449aa0bda60
- Size of remote file:
- 4.99 kB
- SHA256:
- 8aa102aa7f1e9eb678ec173d3a1d45fd596092781e93f28f2ddaff47e1d66c1c
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