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/0299.png from nathanReitinger/MNIST-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 3.25 kB
-
https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0299.png
- Command line
-
hf download hf://nathanReitinger/MNIST-diffusion/samples/0299.png
-
curl -L -o 0299.png https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0299.png
3.25 kB

- Xet hash:
- 3d0a2e9f7c2bd5606b2bf1dbb2fd1ad28774e2e7243e5f68a1afc8d438e5ecb7
- Size of remote file:
- 3.25 kB
- SHA256:
- 4eed3bfe51b3106042350e0b2aa706a05dd0e01dfa47670233a2d6defa027c72
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