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:
- a07dae527dee014478faf7a9c24386751de6d947f64368ca26a714b9121c3178
- Size of remote file:
- 167 MB
- SHA256:
- f7727b5494a1ec3bf57b86c9d0a0f0cb266fba42e6be2840775a6e7347e5a2e5
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