Instructions to use RED-AIGC/StoryMaker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RED-AIGC/StoryMaker with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RED-AIGC/StoryMaker", torch_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

- Xet hash:
- b18fc398bbe89056d84d5d255997288fdb2d24d5633d87d24f158f449579f045
- Size of remote file:
- 5.37 MB
- SHA256:
- 304018fcb18a2e10196d58d84b67b7598c8dfefae7e7cfb53c7e5159f973386b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.