Instructions to use nitrosocke/redshift-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nitrosocke/redshift-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("nitrosocke/redshift-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
Commit History
-
Adding `safetensors` variant of this model
cd22800
-
Correct `sample_size` of Stable Diffusion 1's unet to have correct width and height default (#10)
- Correct `sample_size` of Stable Diffusion 1's unet to have correct width and height default (76e73f69b058b06ca53399af827820ed18250d59) Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>7302e41
-
uploading diffusers (#3)
- Add Diffusers weights for (b09d5930227a8770e0fabe16c7b515b28460641c) Co-authored-by: Kevin <Kevin@users.noreply.huggingface.co>cfa394e