Instructions to use danbrown/ogkalu-comic-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use danbrown/ogkalu-comic-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("danbrown/ogkalu-comic-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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download unet/diffusion_pytorch_model.bin from danbrown/ogkalu-comic-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/danbrown/ogkalu-comic-diffusion/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://danbrown/ogkalu-comic-diffusion/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/danbrown/ogkalu-comic-diffusion/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- d7cf6da37c9c26f37ef14d0ddb3b2ff981e9139b4f42ba295444026793b9b7a7
- Size of remote file:
- 3.44 GB
- SHA256:
- 0cdabd5f0b5b4cd75af0938b7bb331b19c10d45006462dbd54b559d62af5f12b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.