Qwen-Image-Edit-Outfit-2511-SFT

A full-parameter fine-tune of Qwen/Qwen-Image-Edit-2511 for garment / outfit virtual try-on (image editing): given a person photo and a garment photo, the model dresses the person in that outfit.

⚠️ Non-commercial, research use only. See LICENSE. This restriction is inherited from the training data (VITON-HD / IDM-VTON derivatives, CC BY-NC). Do not tag this model Apache-2.0 — the base is Apache-2.0, but the fine-tune carries the upstream NC constraint.

What changed from the base

Only the DiT (transformer) weights were updated via full-parameter SFT. All other components (text encoder, VAE, tokenizer, processor, scheduler) are unchanged from the base Qwen-Image-Edit-2511. So this directory loads exactly like the base model:

from diffusers import QwenImageEditPlusPipeline
import torch
pipe = QwenImageEditPlusPipeline.from_pretrained(
    "lee31221/Qwen-Image-Edit-Outfit-2511-SFT", torch_dtype=torch.bfloat16
).to("cuda")

Training summary

Base	Qwen/Qwen-Image-Edit-2511 (Apache-2.0)
Trainable	DiT only (20.43B params, BF16)
Optimizer	AdamW, lr 1e-5, weight_decay 0.01
Schedule	1 epoch, grad_accum 1, gradient checkpointing on
Data	~11,415 outfit-edit pairs; prompt ≈ 1592 chars (full-text v2 template)
Inputs	image=person, edit_image=garment (condition)
Compute	8× NVIDIA H100 80GB, DeepSpeed ZeRO-3, bf16
Wall-clock	2h22m for 1427 steps (06:41 → 09:03, +08:00)
Throughput	~5.87 s/it, ~1.36 samples/s
Peak VRAM	74.8 GB / GPU (91.7% of 80 GB), 8-GPU balance < 0.9% spread
Loss	0.029 → 0.024 (window mean ↓ 23.7% over training)
Framework	DiffSynth-Studio + Accelerate + DeepSpeed (torch 2.6.0+cu124)

Loss curve was logged to TensorBoard (1427 scalar points). See the run report in the source repository for a full breakdown (memory economics, per-GPU balance, loss noise analysis).

Training data & attribution

Asset	Source	License
Base model (DiT, text encoder, VAE, tokenizer, processor, scheduler)	Qwen/Qwen-Image-Edit-2511	Apache-2.0
Synthetic outfit-edit training pairs	lee31221/Outfit_Qwen-Image-Edit-2511_in_Kling	derived; non-commercial
Underlying person/garment images	VITON-HD	CC BY-NC 4.0
Teacher pipeline (derivative)	IDM-VTON	CC BY-NC-SA 4.0
Training framework	DiffSynth-Studio	Apache-2.0

If you use this model, please attribute Qwen-Image-Edit-2511 and VITON-HD / IDM-VTON.

License

Non-Commercial Research Use only — see LICENSE and NOTICE.md. Commercial use is prohibited. This is stricter than the base model's Apache-2.0, because the fine-tune was trained on CC BY-NC derivatives.

Intended use & limitations

• Intended: academic research on image editing / virtual try-on.
• Not intended: any commercial product, service, or paid feature; generating non-consensual depictions of real people.
• Like all diffusion editors, outputs can be imperfect (garment detail drift, identity changes). Validate on a held-out test set before drawing conclusions.