Instructions to use MirageML/lowpoly-japan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MirageML/lowpoly-japan 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-japan", 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
Commit History
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Add `scale_factor` to vae config. (#2)
- Add `scale_factor` to vae config. (dfada2b4cb53cdd6ef2499084389794cf6257680) Co-authored-by: Suraj Patil <valhalla@users.noreply.huggingface.co>65be623
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Upload vae/diffusion_pytorch_model.bin with huggingface_hub
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Upload vae/config.json with huggingface_hub
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