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

- Xet hash:
- 97dcd897f946e37e5c545fe1ca73e34e5fcb6e2ea46dfb3c37eb392e0eaa3c73
- Size of remote file:
- 1.53 MB
- SHA256:
- 43787ee619b049c2e3aec772b23eae26b30c4b0d2726625e2a4cd4cff0c18e09
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.