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 Settings
- Draw Things
- DiffusionBee
Qwen Edit Head Swap Workflow (No LoRA Training) – 4-Step Lightning Fast What it does: -Swaps heads from source → target image while preserving pose, lighting, and scene context -Runs on Qwen Edit + Lightning LoRA (4 steps) – 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.
#2 opened 11 days ago
by
Tomis221