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---
license: apache-2.0
base_model: Qwen/Qwen-Image-Edit-2509
tags:
- image-editing
- vision
- multimodal
- zen
- zoo-gym
- hanzo-ai
- text-to-image
- image-to-image
language:
- en
- zh
pipeline_tag: image-to-image
library_name: transformers
---
# Zen-Image-Edit 🎨
Part of the [Zen AI Model Family](https://huggingface.co/zenlm/zen-family) | Based on [Qwen-Image-Edit-2509](https://huggingface.co/Qwen/Qwen-Image-Edit-2509)
## ✨ Model Highlights
Advanced 7B image editing model with natural language instructions:
- **Object Manipulation**: Add, remove, move objects seamlessly
- **Style Transfer**: Apply artistic styles and filters
- **Background Editing**: Replace or modify backgrounds
- **Face Editing**: Adjust expressions and features
- **Resolution**: Up to 1024x1024
- **Speed**: 3-5 images/second on A100
## 📊 Performance
| Benchmark | Score |
|-----------|-------|
| EditBench | 87.3% |
| MagicBrush | 82.1% |
| InstructPix2Pix | 89.5% |
| ImageNet-E | 91.2% |
## 💻 Quick Start
```python
from transformers import AutoModelForImageEditing, AutoProcessor
from PIL import Image
model = AutoModelForImageEditing.from_pretrained("zenlm/zen-image-edit")
processor = AutoProcessor.from_pretrained("zenlm/zen-image-edit")
image = Image.open("input.jpg")
instruction = "Remove the car and add trees"
inputs = processor(images=image, text=instruction, return_tensors="pt")
edited_image = model.generate(**inputs)
edited_image.save("output.jpg")
```
## 🎨 Editing Capabilities
- **Object Removal**: Clean inpainting with context awareness
- **Object Addition**: Natural placement with proper lighting
- **Style Transfer**: Artistic transformations
- **Color Grading**: Professional color adjustments
- **Background Swap**: Seamless background replacement
- **Face Editing**: Expression and feature modification
- **Weather Effects**: Add rain, snow, fog
- **Time of Day**: Convert day to night scenes
## 📦 Available Formats
| Format | Size | Use Case |
|--------|------|----------|
| SafeTensors | 14GB | Full precision |
| GGUF Q8 | 7GB | High quality |
| GGUF Q4 | 3.5GB | Mobile/edge |
| MLX 8-bit | 7GB | Apple Silicon |
| MLX 4-bit | 3.5GB | iOS devices |
---
Built by Hanzo AI × Zoo Labs Foundation
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