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license: apache-2.0
base_model: Qwen/Qwen-Image-Edit
tags:
- lora
- diffusers
- image-to-image
- qwen-image-edit
- image-editing
pipeline_tag: image-to-image
---
# Qwen-Image-Edit LoRAs
A collection of LoRA adapters I trained for [Qwen-Image-Edit](https://huggingface.co/Qwen/Qwen-Image-Edit),
focused on pose control and subject consistency in image editing.
The adapters were trained on a mix of collected reference images and synthetic images generated with the
Qwen image model.
## Adapters
| File | Purpose | Rank |
|------|---------|------|
| `qwen-image-edit/multipose_v50_rank96.safetensors` | Multi-pose control (latest) | 96 |
| `qwen-image-edit/multipose_v49h_rank96.safetensors` | Multi-pose control (prior revision) | 96 |
| `qwen-image-edit/qwen_Image_male.safetensors` | Male subject conditioning | - |
## Usage
Load an adapter on top of the Qwen-Image-Edit pipeline with `diffusers`:
```python
from diffusers import QwenImageEditPipeline
import torch
pipe = QwenImageEditPipeline.from_pretrained(
"Qwen/Qwen-Image-Edit", torch_dtype=torch.bfloat16
).to("cuda")
pipe.load_lora_weights(
"lognat0704/diffusion-loras",
weight_name="qwen-image-edit/multipose_v50_rank96.safetensors",
)
# image = pipe(prompt=..., image=...).images[0]
```
## Notes
- Adapters are rank-96 unless noted.
- The `multipose` series iterates on pose-conditioning quality; `v50` is the most recent.
|