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/0033.png from nathanReitinger/MNIST-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 3.88 kB
-
https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0033.png
- Command line
-
hf download hf://nathanReitinger/MNIST-diffusion/samples/0033.png
-
curl -L -o 0033.png https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0033.png
3.88 kB

- Xet hash:
- ce0c3695da00710301875a5680ecfd85ebcec52963b190a8c2fa6ec5149b39dc
- Size of remote file:
- 3.88 kB
- SHA256:
- eacf5cc2bbe4df7ae0df3aa02cd09d5f94650ce1d8777fbf4761ff052b48c390
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