Instructions to use nathanReitinger/MNIST-diffusion-oneImage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nathanReitinger/MNIST-diffusion-oneImage 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-oneImage", 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/45000.png from nathanReitinger/MNIST-diffusion-oneImage: direct link, hf CLI and curl.
- Browser
- Download file 5.74 kB
-
https://huggingface.co/nathanReitinger/MNIST-diffusion-oneImage/resolve/main/samples/45000.png
- Command line
-
hf download hf://nathanReitinger/MNIST-diffusion-oneImage/samples/45000.png
-
curl -L -o 45000.png https://huggingface.co/nathanReitinger/MNIST-diffusion-oneImage/resolve/main/samples/45000.png
5.74 kB

- Xet hash:
- 7ffbc0deaf14282cb1e55a7e275c66bf7d4aea874a3a64bc026e4a44f4f61dbb
- Size of remote file:
- 5.74 kB
- SHA256:
- b1dd80b1c40e24983df90d5b05662b36b3639a137f486e7c770caafb0ab32ae6
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