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/0001.png from nathanReitinger/MNIST-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 6.27 kB
-
https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0001.png
- Command line
-
hf download hf://nathanReitinger/MNIST-diffusion/samples/0001.png
-
curl -L -o 0001.png https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0001.png
6.27 kB

- Xet hash:
- b946d968ab2da8d9b0552ebf03e9fa8f27cca3135f6093b860bc8ff9eaef72a1
- Size of remote file:
- 6.27 kB
- SHA256:
- f9ee2cca126521de19df76463499ca29cd2c3a2f3c4de32ef7e13bed300db0ba
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