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/0025.png from nathanReitinger/MNIST-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0025.png
- Command line
-
hf download hf://nathanReitinger/MNIST-diffusion/samples/0025.png
-
curl -L -o 0025.png https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0025.png
3.96 kB

- Xet hash:
- 7f3e4cc6b5b16a68b07a0712c47db1cac430526272c644743bb0cecfc6badf51
- Size of remote file:
- 3.96 kB
- SHA256:
- 20c8eed0d5c51101ce317ec99301b74d34faeb75ba9d3c0a782ad4a4b4518c81
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