Instructions to use Avrik/mirrors-edge-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Avrik/mirrors-edge-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Avrik/mirrors-edge-diffusion", 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
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license: creativeml-openrail-m
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license: creativeml-openrail-m
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**Mirror's Edge Diffusion**
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A Stable Diffusion model trained on Mirror's Edge screenshots using Dreambooth.
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Use the prompt **MirrorsEdge style**. Other notable tokens are **abstract**, **floating shapes**, **cityscape** and **back rooms**.
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If your outputs are too random and geometric, try adding **abstract** and **floating shapes** to the negative prompt.
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