Instructions to use alfredplpl/emi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use alfredplpl/emi with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("alfredplpl/emi", 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:
- ece96eac5b810c13bc93f832c667162675ef139d7ce00c7029b31a2ea35c6698
- Size of remote file:
- 1.73 MB
- SHA256:
- 950a629ab7fd4b3614215718cf97cac7fc29fe035ebb89ebb482371c36955e50
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.