Instructions to use olesheva/head_swap_qwen_edit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use olesheva/head_swap_qwen_edit with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("olesheva/head_swap_qwen_edit") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
head_swap_qwen_edit

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Model description
Qwen Edit Head Swap Workflow (No LoRA Training) โ 4-Step Lightning Fast
What it does:
-Swaps heads from source โ target image while preserving pose, lighting, and scene context
-Runs on Qwen Edit + Lightning LoRA (4 steps) โ super fast
-Automatic face masking, cropping, and intelligent blending
-Smart system prompts generated from both images via vision models
-ControlNet + depth/structure for alignment control
-Final upscale with SeedVR2 for clean, polished output.
Download model
Download them in the Files & versions tab.
- Downloads last month
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Model tree for olesheva/head_swap_qwen_edit
Base model
Qwen/Qwen-Image