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 Settings
- Draw Things
- DiffusionBee

- Xet hash:
- d55681c419bca30086b27bf2959ff222a7fe55b3d22898203bff2f9a710736bb
- Size of remote file:
- 36.4 kB
- SHA256:
- 79aca73ae0bad5eabedb43da1975f1b20b721ae57e17212c2cf7baefcfa750d9
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