Instructions to use Disty0/sd3_randn_aura_vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Disty0/sd3_randn_aura_vae with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Disty0/sd3_randn_aura_vae", 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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README.md
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An anime model trained on randomly initialized SD3 Transformer weights with RMSNorm and AuraDiffusion 16ch VAE.
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Trained on 256px resolutions using anime dataset.
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Requires Diffusers with RMSNorm
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An anime model trained on randomly initialized SD3 Transformer weights with RMSNorm and AuraDiffusion 16ch VAE.
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Trained on 256px resolutions using anime dataset.
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Requires Diffusers with RMSNorm support: https://github.com/Disty0/diffusers/tree/sd3_rms_norm
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