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/0011.png from nathanReitinger/MNIST-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 5.1 kB
-
https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0011.png
- Command line
-
hf download hf://nathanReitinger/MNIST-diffusion/samples/0011.png
-
curl -L -o 0011.png https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0011.png
5.1 kB

- Xet hash:
- d2a9e4b67e324672ed4c72ceddb75f6282e689d31a9c8725f680bb461d569b32
- Size of remote file:
- 5.1 kB
- SHA256:
- cd8d0758fe3b6d854355e429049723946ceecc6ba877315336c55d62ea871b75
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