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--- |
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license: apache-2.0 |
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base_model: |
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- Qwen/Qwen-Image-Edit |
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language: |
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- en |
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- zh |
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library_name: diffusers |
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pipeline_tag: image-to-image |
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datasets: |
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- OPPOer/X2Edit-Dataset |
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--- |
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<div align="center"> |
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<h1>Qwen-Image-Edit-Pruning</h1> |
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<a href='https://github.com/OPPO-Mente-Lab/Qwen-Image-Pruning'><img src="https://img.shields.io/badge/GitHub-OPPOer-blue.svg?logo=github" alt="GitHub"></a> |
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</div> |
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## Update |
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- 2025/10/09: We release **[Qwen-Image-Edit-2509-Pruning-13B-4steps](https://huggingface.co/OPPOer/Qwen-Image-Edit-2509-Pruning)** |
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- 2025/09/29: We release **[Qwen-Image-Edit-2509-Pruning-14B](https://huggingface.co/OPPOer/Qwen-Image-Edit-2509-Pruning)** |
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- 2025/09/28: We release **[Qwen-Image-Edit-Pruning-13B-4steps](https://huggingface.co/OPPOer/Qwen-Image-Edit-Pruning)** |
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## Introduction |
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This open-source project is based on Qwen-Image-Edit and has attempted model pruning, removing 20 layers while retaining the weights of 40 layers, resulting in a model size of 13.6B parameters. The pruned version will continue to be iterated upon. Please stay tuned. |
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<div align="center"> |
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<img src="bench-2509.png"> |
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</div> |
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## Quick Start |
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Install the latest version of diffusers and pytorch |
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``` |
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pip install torch |
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pip install git+https://github.com/huggingface/diffusers |
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``` |
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### Qwen-Image-Edit-2509-14B Inference |
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```python |
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import os |
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import torch |
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from PIL import Image |
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from diffusers import QwenImageEditPlusPipeline |
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model_name = f"OPPOer/Qwen-Image-Edit-2509-Pruning" |
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pipeline = QwenImageEditPlusPipeline.from_pretrained(model_name, torch_dtype=torch.bfloat16) |
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print("pipeline loaded") |
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pipeline.to('cuda') |
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pipeline.set_progress_bar_config(disable=None) |
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image1 = Image.open("input1.jpg") |
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image2 = Image.open("input2.jpg") |
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prompt = "Let the ancient costume beauty in the second picture sit on the sofa in the first picture" |
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inputs = { |
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"image": [image1, image2], |
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"prompt": prompt, |
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"generator": torch.manual_seed(0), |
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"true_cfg_scale": 4.0, |
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"negative_prompt": " ", |
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"num_inference_steps": 40, |
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"guidance_scale": 1.0, |
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"num_images_per_prompt": 1, |
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} |
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with torch.inference_mode(): |
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output = pipeline(**inputs) |
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output_image = output.images[0] |
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output_image.save("output_image_edit_plus.png") |
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print("image saved at", os.path.abspath("output_image_edit_plus.png")) |
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``` |
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### Qwen-Image-Edit-2509-13B Inference |
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```python |
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import os |
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import torch |
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from PIL import Image |
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from diffusers import QwenImageEditPlusPipeline |
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model_name = f"OPPOer/Qwen-Image-Edit-2509-Pruning/Qwen-Image-Edit-2509-13B-4steps" |
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pipeline = QwenImageEditPlusPipeline.from_pretrained(model_name, torch_dtype=torch.bfloat16) |
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print("pipeline loaded") |
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pipeline.to('cuda') |
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pipeline.set_progress_bar_config(disable=None) |
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image1 = Image.open("input1.jpg") |
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image2 = Image.open("input2.jpg") |
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prompt = "Let the ancient costume beauty in the second picture sit on the sofa in the first picture" |
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inputs = { |
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"image": [image1, image2], |
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"prompt": prompt, |
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"generator": torch.manual_seed(0), |
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"true_cfg_scale": 1.0, |
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"negative_prompt": " ", |
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"num_inference_steps": 4, |
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"guidance_scale": 1.0, |
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"num_images_per_prompt": 1, |
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} |
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with torch.inference_mode(): |
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output = pipeline(**inputs) |
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output_image = output.images[0] |
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output_image.save("output_image_edit_plus.png") |
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print("image saved at", os.path.abspath("output_image_edit_plus.png")) |
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``` |
