Unconditional Image Generation
Diffusers
TensorBoard
Safetensors
PyTorch
DDPMPipeline
diffusion-models-class
Instructions to use 1aurent/ddpm-mnist with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 1aurent/ddpm-mnist with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("1aurent/ddpm-mnist", 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 diffusion_pytorch_model.bin from 1aurent/ddpm-mnist: direct link, hf CLI and curl.
- Browser
- Download file 4.35 MB
-
https://huggingface.co/1aurent/ddpm-mnist/resolve/refs%2Fpr%2F1/diffusion_pytorch_model.bin
- Command line
-
hf download hf://1aurent/ddpm-mnist@refs/pr/1/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/1aurent/ddpm-mnist/resolve/refs%2Fpr%2F1/diffusion_pytorch_model.bin
4.35 MB
- Xet hash:
- 6a6fa3d85d683cd6f4997bcaca7c14fdbc1a9e8616ea3709315179be3a1c972b
- Size of remote file:
- 4.35 MB
- SHA256:
- 03e018efaf5d396e39f856d676a62896347f0b8dfff451fc97e6d068321d9462
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