README.md

---
license: other
license_name: fair-ai-public-license-1.0-sd
license_link: https://freedevproject.org/faipl-1.0-sd/
datasets:
- KBlueLeaf/danbooru2023-webp-4Mpixel
- KBlueLeaf/danbooru2023-sqlite
language:
- en
library_name: diffusers
pipeline_tag: text-to-image
---

# Kohaku XL Epsilon rev2
join us: https://discord.gg/tPBsKDyRR5

## Rev2 Features
- Resumed from Kohaku XL Epsilon rev1
- 1.56M images, 5epoch
- Trained on selected artists' artworks and images about selected series/games
- Trained on PVC figure photos, can generate PVC style without any additional models

## Usage (PLEASE READ THIS SECTION)
### Prompt Format
`<1girl/1boy/1other/...>, <character>, <series>, <artists>, <general tags>, <quality tags>, <year tags>, <meta tags>, <rating tags>`

### Special Tags
- Quality tags: masterpiece, best quality, great quality, good quality, normal quality, low quality, worst quality
- Rating tags: safe, sensitive, nsfw, explicit
- Date tags: newest, recent, mid, early, old

#### Rating tags
General: safe
Sensitive: sensitive
Questionable: nsfw
Explicit: nsfw, explicit

### Resolution
This model is trained for resolutions from ARB 1024x1024 with minimum resolution 256 and maximum resolution 4096. This means you can use the standard SDXL resolution. However, opting for a slightly higher resolution than 1024x1024 is recommended. Applying a hires-fix is also suggested for better results.

## Training
- Hardware: Quad RTX 3090s
- Num Train Images: 1,536,902
- Total Epoch: 5
- Total Steps: 15015
- Training Time: 410 hours (wall time)
- Batch Size: 4
- Grad Accumulation Step: 32
- Equivalent Batch Size: 512
- Optimizer: Lion8bit
- Learning Rate: 1e-5 for UNet / 2e-6 for TE
- LR Scheduler: Cosine (with warmup)
- Warmup Steps: 1000
- Weight Decay: 0.1
- Betas: 0.9, 0.95
- Min SNR Gamma: 5
- Noise Offset: 0.0357
- Resolution: 1024x1024
- Min Bucket Resolution: 256
- Max Bucket Resolution: 4096
- Mixed Precision: FP16
- Caption Tag Dropout: 0.2
- Caption Dropout: 0.05

## License:
Fair-AI-public-1.0-sd