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:
- ea7b666d8841c54a63e0de1a76b0258cef48d888fa1344050abe20f770d95a6f
- Size of remote file:
- 1.38 MB
- SHA256:
- 537f0f2a6e7ba2670c3474fcd4052f43bf7daf5acea9648ab65d3ee827be5151
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