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
- Draw Things
- DiffusionBee
Low Poly Landscape on Stable Diffusion via Dreambooth
This the Stable Diffusion model fine-tuned the Low Poly Landscape concept taught to Stable Diffusion with Dreambooth.
It can be used by modifying the instance_prompt: a photo of lowpoly_landscape
Run on Mirage
Run this model and explore text-to-3D on Mirage!
Here are is a sample output for this model:

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