Instructions to use shalpin87/diffusion_cifar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use shalpin87/diffusion_cifar with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("shalpin87/diffusion_cifar", 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 unet/diffusion_pytorch_model.bin from shalpin87/diffusion_cifar: direct link, hf CLI and curl.
- Browser
- Download file 455 MB
-
https://huggingface.co/shalpin87/diffusion_cifar/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://shalpin87/diffusion_cifar/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/shalpin87/diffusion_cifar/resolve/main/unet/diffusion_pytorch_model.bin
455 MB
- Xet hash:
- c214df858987319b3faf0ce6f30937c4a5d3ea3aa034ed97c705bcb7682b295f
- Size of remote file:
- 455 MB
- SHA256:
- 8418ca5333b42f03d1b6f220494bd91fa3f5f87e4de040463a485b0d449f4235
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.