Instructions to use maximalmargin/aem100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use maximalmargin/aem100 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("maximalmargin/aem100", 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:
- 396bce8df6dd34b1306f28ac8779bcb552841335fe9034c957afb731e06dcf6c
- Size of remote file:
- 3.46 GB
- SHA256:
- 30b8316666e1f6396b315bb21adf74f255e34d44ce261dae799f5c462f6befaf
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