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/0030.png from nathanReitinger/MNIST-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 3.87 kB
-
https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0030.png
- Command line
-
hf download hf://nathanReitinger/MNIST-diffusion/samples/0030.png
-
curl -L -o 0030.png https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0030.png
3.87 kB

- Xet hash:
- ef84869b322ed1440944b0075fa2007e29b538386cd256db639b414c111460ed
- Size of remote file:
- 3.87 kB
- SHA256:
- 91b57be122cfe1a68e482a319eeb3fd3280f2c9a9aee5f182a4391b64362d916
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