Illustration 1.0 — Qwen-Image (Baseline)
The monotonic-training counterpart to alvdansen/illustration-1.0-qwen-image. Same 244-image dataset, same hyperparameters, same hardware — trained without the chained dataset rotation. Published alongside the chained version so the paired comparison in Forgetting on Purpose is reproducible. Read the paper · Source on GitHub.
For general use, the chained version is the better pick. This one is here for anyone who wants to run their own comparison.
Usage
No trigger word. Same inference recipe as the chained twin:
Sampler: euler
Scheduler: simple
CFG: 3.5
Steps: 45
LoRA strength: 0.8–1.0
Training Details
- Base model: Qwen-Image (FP8 quantized, text encoder FP8)
- Training steps: 59,000, monotonic full-dataset training from step zero
- Rank/Alpha: 42/42
- Learning rate: 5e-5
- Optimizer: AdamW 8-bit
- Caption dropout: 0.35
- EMA: enabled (decay 0.99)
- Noise scheduler: flowmatch
- Precision: bf16 with qfloat8 quantization
- Dataset: same 244-image combined dataset as the chained twin
- Trainer: ai-toolkit by Ostris
- Hardware: NVIDIA RTX 6000 Ada (A6000, 48 GB VRAM)
Identical to the chained twin in every parameter except the dataset schedule.
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Model tree for alvdansen/illustration-1.0-qwen-image-baseline
Base model
Qwen/Qwen-Image