File size: 1,561 Bytes
43764fb 6aa0743 43764fb 6aa0743 43764fb 6aa0743 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | ---
base_model: Qwen/Qwen-Image-Edit-2511
library_name: peft
license: apache-2.0
tags:
- lora
- diffusion
- image-editing
- product-consistency
- grpo
- reinforcement-learning
---
# ReCoEdit — RL LoRA Adapter (Epoch 24)
LoRA adapter for **Qwen-Image-Edit-2511**, trained with Flow-GRPO and a product consistency reward.
Plug this into `Qwen/Qwen-Image-Edit-2511` to get a model that better preserves product identity (color, shape, logo) during image editing.
- **Base model**: `Qwen/Qwen-Image-Edit-2511`
- **Training**: GRPO (Group Relative Policy Optimization) on e-commerce product editing data
- **Reward**: Qwen3-VL-30B-A3B-Instruct as VLM judge, 1-5 product consistency score
- **Result**: Reward improved from 0.022 → 0.480 (21.8× over SFT baseline)
- **LoRA rank / alpha**: 64 / 128
- **Checkpoint**: Epoch 24 (peak performance)
## Usage
```python
from peft import PeftModel
from huggingface_hub import snapshot_download
# Load base model (via DiffSynth-Studio)
# See https://github.com/Matteoooo46/ReCoEdit for full inference script
lora_path = snapshot_download("Matteoooo46/ReCoEdit-RL")
pipe.load_lora(pipe.dit, lora_path + "/adapter_model.safetensors")
```
See the [ReCoEdit repository](https://github.com/Matteoooo46/ReCoEdit) for the complete inference pipeline including APG guidance and prompt rewriter.
## Citation
```bibtex
@misc{recoedit2025,
title={ReCoEdit: Rewriter-Guided Consistency Alignment for Product Image Editing},
author={},
year={2025},
howpublished={\url{https://github.com/Matteoooo46/ReCoEdit}},
}
```
|