Instructions to use Zaytron40k/Qwen-Image-RenderStyle-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Inference
- Notebooks
- Google Colab
- Kaggle
Qwen-Image (base) LoRA - Render Style (t01nstyle)
A base Qwen-Image (t2i) LoRA that locks in the t01nstyle render aesthetic (shading, linework, skin rendering). Stackable on the Qwen-Image-Edit-2511 pipeline to reinforce style. Trained with DiffSynth-Studio on 337 t01nstyle images.
Trigger: t01nstyle (prepend to the prompt). Trained with dual captions
(50% full description + 50% trigger-only) to bind the style to the trigger.
Training config
| base | Qwen/Qwen-Image (DiT only, t2i) |
| rank / lr | 32 / 1e-4 |
| epochs x steps | 10 x 674 (337 imgs, dual-caption, repeat 1) |
| resolution | max_pixels 1763584 (~1328^2) |
| precision | bf16 + gradient checkpointing |
Loss
| epoch | step | EMA loss min |
|---|---|---|
| 0 | 1 | 0.0478 <- global min |
| 1 | 1092 | 0.0654 |
| 2 | 1494 | 0.0659 |
| 3 | 2602 | 0.0679 |
| 4 | 2854 | 0.0661 |
| 5 | 3981 | 0.0657 |
| 6 | 4560 | 0.0642 |
| 7 | 5352 | 0.0610 |
| 8 | 5773 | 0.0640 |
| 9 | 6179 | 0.0670 |
Loss is flat/noisy (normal) - pick the checkpoint by visual eval on WaveSpeed, not by loss.
Model tree for Zaytron40k/Qwen-Image-RenderStyle-LoRA
Base model
Qwen/Qwen-Image