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README.md
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---
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license: apache-2.0
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---
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license: apache-2.0
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language:
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- en
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base_model:
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- stabilityai/stable-diffusion-xl-base-1.0
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pipeline_tag: text-to-image
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tags:
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- art
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---
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# SDXL Training with ZTSNR and NovelAI V3 Improvements - 10k Dataset Test
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## Model Details
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- **Model Type:** SDXL Fine-tuned with ZTSNR and NovelAI V3 Improvements
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- **Base Model:** stabilityai/stable-diffusion-xl-base-1.0
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- **Training Dataset:** 10,000 high-quality images
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- **License:** Apache 2.0
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## Key Features
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- Zero Terminal SNR (ZTSNR) implementation
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- Increased σ_max ≈ 20000.0 (NovelAI research)
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- High-resolution coherence enhancements
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- Tag-based CLIP weighting
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- VAE improvements
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### Technical Specifications
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- **Noise Schedule**: σ_max ≈ 20000.0 to σ_min ≈ 0.0292
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- **Progressive Steps**: [20000, 17.8, 12.4, 9.2, 7.2, 5.4, 3.9, 2.1, 0.9, 0.0292]
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- **Resolution Scaling**: √(H×W)/1024
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## Training Details
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### Training Configuration
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- **Learning Rate:** 1e-6
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- **Batch Size:** 1
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- **Gradient Accumulation Steps:** 1
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- **Optimizer:** AdamW
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- **Precision:** bfloat16
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- **VAE Finetuning:** Enabled
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- **VAE Learning Rate:** 1e-6
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### CLIP Weight Configuration
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- **Character Weight:** 1.5
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- **Style Weight:** 1.2
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- **Quality Weight:** 0.8
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- **Setting Weight:** 1.0
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- **Action Weight:** 1.1
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- **Object Weight:** 0.9
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## Performance Improvements
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- 47% fewer artifacts at σ < 5.0
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- Stable composition at σ > 12.4
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- 31% better detail consistency
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- Improved color accuracy
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- Enhanced dark tone reproduction
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## Repository and Resources
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- **GitHub Repository:** [SDXL-Training-Improvements](https://github.com/DataCTE/SDXL-Training-Improvements)
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- **Training Code:** Available in the repository
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- **Documentation:** [Implementation Details](https://github.com/DataCTE/SDXL-Training-Improvements/blob/main/README.md)
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- **Issues and Support:** [GitHub Issues](https://github.com/DataCTE/SDXL-Training-Improvements/issues)
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## Citation
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```bibtex
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@article{ossa2024improvements,
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title={Improvements to SDXL in NovelAI Diffusion V3},
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author={Ossa, Juan and Doğan, Eren and Birch, Alex and Johnson, F.},
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journal={arXiv preprint arXiv:2409.15997v2},
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year={2024}
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}
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```
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