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/0018.png from nathanReitinger/MNIST-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 3.98 kB
-
https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0018.png
- Command line
-
hf download hf://nathanReitinger/MNIST-diffusion/samples/0018.png
-
curl -L -o 0018.png https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0018.png
3.98 kB

- Xet hash:
- 783d71be80d353faa7b4c423e2fc428271df23ce5c772b1fc6b6b3e40fc59af2
- Size of remote file:
- 3.98 kB
- SHA256:
- 3e26ccfdebf2df2fd189fca0b53c8b4c3459289175a9efdf1a1179426ec599b4
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