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/0012.png from nathanReitinger/MNIST-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 4.83 kB
-
https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0012.png
- Command line
-
hf download hf://nathanReitinger/MNIST-diffusion/samples/0012.png
-
curl -L -o 0012.png https://huggingface.co/nathanReitinger/MNIST-diffusion/resolve/main/samples/0012.png
4.83 kB

- Xet hash:
- 46a7f3a5c30091b036f0b95d4c864890dfcc98dd68cf772c6bbf85880d4bb61d
- Size of remote file:
- 4.83 kB
- SHA256:
- c5efad82f37c5ca5e7762f6f2a73e6b9f8d1257380cb4cdb9e09feb0dc5a4f76
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