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