Instructions to use MirageML/lowpoly-landscape with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MirageML/lowpoly-landscape with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MirageML/lowpoly-landscape", 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:
- cb160a9c62143c6903a75068634a23bc5531a1bf00a8802c3f8cefa08c127bb3
- Size of remote file:
- 492 MB
- SHA256:
- 964bbb847e843f95fa732f13ead7f6e5bf4cfa2a917622171cf6f1c617cf3463
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