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2511-surgical-v3-t01nstyle
Zaytron40k/2511-surgical-v3-t01nstyle
2511-surgical-v3-t01nstyle is a machine learning model from Zaytron40k. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Style LoRA trained in T2I mode (--modelversion original) on Edit-2511 weights with image-stream-only surgical targeting (image-stream AdaLN modulation + image-stream MLP down-projection). Designed to preserve native m…
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Updated May 8, 2026
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- May 8, 2026
- Updated
- May 8, 2026
- SHA
- f549151e
Base models
Model card
From the Hugging Face model README
t01nstyle LoRA for Qwen-Image-Edit-2511 (surgical v3)
Style LoRA trained in T2I mode (--model_version original) on Edit-2511 weights with image-stream-only surgical targeting (image-stream AdaLN modulation + image-stream MLP down-projection). Designed to preserve native multi-reference editing and InstantX ControlNet compatibility.
Status: training complete (22 epochs).
Trigger: t01nstyle
Recommended checkpoint
Start with t01nstyle_qie2511_t2i_surgical_v3-000009.safetensors (global minimum loss at epoch 9: 0.07330). A/B test against epochs +/- 2 by visual quality.
Per-epoch loss
| epoch | loss |
|---|---|
| 1 | 0.07905 |
| 2 | 0.07744 |
| 3 | 0.07633 |
| 4 | 0.07643 |
| 5 | 0.07635 |
| 6 | 0.07627 |
| 7 | 0.07951 |
| 8 | 0.07611 |
| 9 | 0.07330 (min) |
| 10 | 0.07634 |
| 11 | 0.07681 |
| 12 | 0.07656 |
| 13 | 0.07567 |
| 14 | 0.07650 |
| 15 | 0.07673 |
| 16 | 0.07683 |
| 17 | 0.07779 |
| 18 | 0.07532 |
| 19 | 0.07647 |
| 20 | 0.07490 |
| 21 | 0.07601 |
| 22 | 0.07713 |
Loss curve typically very flat for surgical LoRA (small parameter count). Visual quality at lora_scale 1.0 is the deciding factor.
Targeting (v3)
Two patterns (vs three in v1):
img_mod.1- image-stream AdaLN modulationimg_mlp.net.2- image-stream MLP down-projection
120 LoRA modules total (60 transformer blocks x 2). All attention projections (to_q/k/v, to_out.0, add_q/k/v_proj, to_add_out) are bit-identical to base Edit-2511. MLP up-projection (img_mlp.net.0.proj) and entire text-stream untouched.
Inference
- Pipeline: Qwen-Image-Edit-2511 (multi-reference)
- Compatible with InstantX ControlNet for Qwen-Image (use
controlnet_conditioning_scale 0.6-0.8) - LoRA scale: 1.0 (surgical LoRA - full strength expected)
- Sampler: FlowMatch / Euler, 25-40 steps, true CFG 4.0
- Resolution: 1024^2 or native 1328^2
Training
- Tuner: musubi-tuner (kohya-ss),
--model_version originalon Edit-2511 weights - Dataset: 256 art images in t01nstyle, T2I captions (no control images)
- Network: rank 16 / alpha 16
- Learning rate: 5e-5 (adamw8bit, constant_with_warmup, 200 warmup steps)
- Timestep sampling: shift, discrete_flow_shift 2.2, num_timestep_buckets 8
- 22 epochs, ~3036 steps
- Hardware: H100 SXM 80GB (bf16, sdpa)
The unnumbered t01nstyle_qie2511_t2i_surgical_v3_final.safetensors corresponds to epoch 22.
Files
- t01nstyle_qie2511_t2i_surgical_v3-NNNNNN.safetensors - checkpoints per epoch
- train.sh - full training command
- dataset.toml - dataset configuration
- training.log - full training log
- tensorboard/ - tensorboard event files for loss curves
- License
- apache-2.0
- Created
- May 8, 2026
- Updated
- May 8, 2026