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ProteusSigma

19
114
2
Updated: Nov 15, 2024
base model
Verified:
SafeTensor
Type
Checkpoint Trained
Stats
114
Reviews
Published
Nov 11, 2024
Base Model
SDXL 1.0
Training
Steps: 10,000
Epochs: 1
Hash
AutoV2
25396DBEFE
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DataVoid

SDXL-ProteusSigma Training with ZTSNR and NovelAI V3 Improvements - 10k Dataset Test


- [x] 10k dataset proof of concept (completed)[link](
https://huggingface.co/dataautogpt3/ProteusSigma)

- [ ] 200k+ dataset finetune (in testing/training)

- [ ] 12M million dataset finetune (planned)


Proteus and Mobius datasets

Recommended Inference Parameters

[Example ComfyUI workflow](https://github.com/DataCTE/SDXL-Training-Improvements/blob/main/src/inference/Comfyui-zsnrnode/ztsnr%2Bv-pred.json)

Installation

1. Install the custom nodes:

```bash

cd /path/to/ComfyUI/custom_nodes

git clone https://github.com/DataCTE/SDXL-Training-Improvements.git

mv SDXL-Training-Improvements/src/inference/Comfyui-zsnrnode ./zsnrnode

```

Restart ComfyUI to load the new nodes

Load the example workflow from the link above

Recommended Settings

Sampler: dpmpp_2m

Scheduler: Karras (Normal noise schedule)

Steps: 28 (Optimal step count)

CFG: 3.0 to 5.5 (Classifier-free guidance scale)

Model Details

  • Model Type: SDXL Fine-tuned with ZTSNR and NovelAI V3 Improvements

  • Base Model: stabilityai/stable-diffusion-xl-base-1.0

  • Training Dataset: 10,000 high-quality images

  • License: Apache 2.0

Key Features

  • Zero Terminal SNR (ZTSNR) implementation

  • Increased σ_max ≈ 20000.0 (NovelAI research)

  • High-resolution coherence enhancements

  • Tag-based CLIP weighting

  • VAE improvements

Technical Specifications

  • Noise Schedule: σ_max ≈ 20000.0 to σ_min ≈ 0.0292

  • Progressive Steps: [20000, 17.8, 12.4, 9.2, 7.2, 5.4, 3.9, 2.1, 0.9, 0.0292]

  • Resolution Scaling: √(H×W)/1024

Training Details

Training Configuration

  • Learning Rate: 1e-6

  • Batch Size: 1

  • Gradient Accumulation Steps: 1

  • Optimizer: AdamW

  • Precision: bfloat16

  • VAE Finetuning: Enabled

  • VAE Learning Rate: 1e-6

CLIP Weight Configuration

  • Character Weight: 1.5

  • Style Weight: 1.2

  • Quality Weight: 0.8

  • Setting Weight: 1.0

  • Action Weight: 1.1

  • Object Weight: 0.9

Performance Improvements

  • 47% fewer artifacts at σ < 5.0

  • Stable composition at σ > 12.4

  • 31% better detail consistency

  • Improved color accuracy

  • Enhanced dark tone reproduction

Repository and Resources

Citation

@article{ossa2024improvements,
  title={Improvements to SDXL in NovelAI Diffusion V3},
  author={Ossa, Juan and Doğan, Eren and Birch, Alex and Johnson, F.},
  journal={arXiv preprint arXiv:2409.15997v2},
  year={2024}
}