Improve model card: Add license, pipeline tag, library name, paper, project, and code links
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by
nielsr
HF Staff
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README.md
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license:
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---
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license: cc-by-nc-4.0
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pipeline_tag: image-to-image
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library_name: transformers
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---
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<p align="center">
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<img src="https://github.com/xiaomi-research/lego-edit/raw/main/resources/lego_pic.png" alt="Lego-Edit" width="240"/>
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</p>
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<p align="center">
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<a href="https://xiaomi-research.github.io/lego-edit/">
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<img
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src="https://img.shields.io/static/v1?label=Project%20Page&message=Web&color=green"
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alt="Lego-Edit Website"
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/>
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</a>
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<a href="https://arxiv.org/abs/2509.12883">
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<img
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src="https://img.shields.io/static/v1?label=Tech%20Report&message=Arxiv&color=red"
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alt="Lego-Edit Paper on arXiv"
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/>
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</a>
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<a href="https://huggingface.co/xiaomi-research/lego-edit">
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<img
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src="https://img.shields.io/static/v1?label=Model&message=HuggingFace&color=yellow"
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alt="Lego-Edit Model"
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/>
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</a>
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<a href="https://editdemo.ai.xiaomi.net/">
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<img
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src="https://img.shields.io/badge/Demo-Live-orange"
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alt="Lego-Edit Demo"
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/>
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</a>
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</p>
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# Lego-Edit: A General Image Editing Framework with Model-Level Bricks and MLLM Builder
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This repository contains the model weights for **Lego-Edit**, a general image editing framework presented in the paper [Lego-Edit: A General Image Editing Framework with Model-Level Bricks and MLLM Builder](https://huggingface.co/papers/2509.12883).
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**Project Page**: [https://xiaomi-research.github.io/lego-edit/](https://xiaomi-research.github.io/lego-edit/)
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**GitHub Repository**: [https://github.com/xiaomi-research/lego-edit](https://github.com/xiaomi-research/lego-edit)
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**Live Demo**: [https://editdemo.ai.xiaomi.net/](https://editdemo.ai.xiaomi.net/)
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## Abstract
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Instruction-based image editing has garnered significant attention due to its direct interaction with users. However, real-world user instructions are immensely diverse, and existing methods often fail to generalize effectively to instructions outside their training domain, limiting their practical application. To address this, we propose Lego-Edit, which leverages the generalization capability of Multi-modal Large Language Model (MLLM) to organize a suite of model-level editing tools to tackle this challenge. Lego-Edit incorporates two key designs: (1) a model-level toolkit comprising diverse models efficiently trained on limited data and several image manipulation functions, enabling fine-grained composition of editing actions by the MLLM; and (2) a three-stage progressive reinforcement learning approach that uses feedback on unannotated, open-domain instructions to train the MLLM, equipping it with generalized reasoning capabilities for handling real-world instructions. Experiments demonstrate that Lego-Edit achieves state-of-the-art performance on GEdit-Bench and ImgBench. It exhibits robust reasoning capabilities for open-domain instructions and can utilize newly introduced editing tools without additional fine-tuning. The figure below showcases Lego-Edit's qualitative performance.
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<p align="center"><img src="https://github.com/xiaomi-research/lego-edit/raw/main/resources/case_pic.png" width="95%"></p>
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## β¨ Features
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Lego-Edit supports local editing, global editing, and multi-step editing as demonstrated in our tests, with corresponding results shown above. We discuss its feedback responsiveness and tool-extension capabilities in our paper.
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Additionally, Lego-Edit accepts mask inputs for precise editing region control. Example applications are provided here:
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<p align="center"><img src="https://github.com/xiaomi-research/lego-edit/raw/main/resources/maskcase1.png" width="95%"></p>
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<p align="center"><img src="https://github.com/xiaomi-research/lego-edit/raw/main/resources/maskcase2.png" width="95%"></p>
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You can try it and find more usages of this framework.
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## π’ News
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- **Sep 17, 2025:** We released the [demo](https://editdemo.ai.xiaomi.net/), [model](https://huggingface.co/xiaomi-research/lego-edit), and [report](https://arxiv.org/abs/2509.12883) for Lego-Edit.
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## π₯ Quick Start
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1οΈβ£ Set up environment
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```bash
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conda create -n legoedit python==3.11
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conda activate legoedit
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pip install -r ./requirements.txt
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Install flash-attention (you can install the corresponding version of flash-attention at https://github.com/Dao-AILab/flash-attention/releases)
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Modify ~/yourconda/envs/lego-edit/lib/python3.11/site-packages/transformers/modeling_utils.py, line 5105, map_location="meta" to map_location="cpu"
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```
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2οΈβ£ Download pretrained checkpoint and custom nodes
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Custom Nodes:
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```bash
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cd custom_nodes
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git clone https://github.com/chflame163/ComfyUI_LayerStyle.git
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git clone https://github.com/Fannovel16/comfyui_controlnet_aux.git
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```
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Base Model:
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1. Download the [FLUX.1-Fill-dev](https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev/blob/main/flux1-fill-dev.safetensors) and [FLUX.1-Canny-dev](https://huggingface.co/black-forest-labs/FLUX.1-Canny-dev/blob/main/flux1-canny-dev.safetensors) and copy them to './models/unet/'.
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2. Download the [vae](https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev/blob/main/ae.safetensors) and copy it to './models/vae/'.
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3. Download the [clip_l](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/clip_l.safetensors) and [t5xxl](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/t5xxl_fp8_e4m3fn.safetensors) and copy them to './models/clip/'.
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4. Download the [lama](https://drive.google.com/file/d/11RbsVSav3O-fReBsPHBE1nn8kcFIMnKp/view?usp=drive_link), unzip and copy it to './lama'.
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Our Model:
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1. Download all the models (Builder, mimo_lora, CVSOS, CVRES, loras) from [lego-edit](https://huggingface.co/xiaomi-research/lego-edit/).
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Your model structure should match the following:
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```bash
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βββ README.md
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βββ requirements.txt
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βββ legodemo.py
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βββ Builder/
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βββ mimo_lora/
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βββ models/
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β βββ unet/
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β βββ vae/
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β βββ clip/
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β βββ loras/
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βββ CVSOS/
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βββ CVRES/
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βββ lama/
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β βββ big-lama/
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```
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3οΈβ£ Use Gradio WebUI to start playing with Lego-Edit!
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```bash
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python legodemo.py
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```
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## πΌ New Tools Integration
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Our Lego-Edit supports the integration of new tools. You can follow the steps below to add custom tools, and The Builder will be able to use them during image editing.
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1οΈβ£ Add the custom tools in system_prompt.txt
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In system_prompt.txt, you can see many tools such as FASTINPAINT, FLUX-FILL, and more. You can add new tools to perform your desired editing tasks. For example, after the FLUX-POSE tool, you could define a new FLUX-SR tool to handle image super-resolution. In system_prompt.txt, you only need to add the model's description, inputs, outputs and constraints, as shown below:
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```bash
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...
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10.FLUX-POSE (Change the object's posture, expression, etc.)
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Input: {Image[image], Str[prompt]}
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Output: {Image[image]}
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Constraint: The input prompt must provide a detailed description of the external characteristics of the modification target, such as gender, clothing, accessories, etc and don't use any PREDICT model in advance.
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11.FLUX-BRIGHT (Input image and ratio, adjust image brightness according to ratio)
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Input: {Image[image], Float[ratio]}
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Output: {Image[image]}
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Constraint: The range of input ratio is > 0, where 0 represents the darkest, 0.5 represents it remains unchanged and > 0.5 represents the brighter.
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**Actual example1:**
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...
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```
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2οΈβ£ Add the tool function in legodemo.py
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In the initialize_model_mapping function within legodemo.py, add the function name of your new tool.
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```python
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def initialize_model_mapping(self) -> Dict[str, Any]:
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return {
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"CMI-PRED": self.dummy_captionmask_pred,
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"RES": self.dummy_res,
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"MASK-SEG": self.dummy_mask_seg,
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"FASTINPAINT": self.dummy_fastinpaint,
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"FLUX-FILL": self.dummy_flux_fill,
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"FLUX-INPAINT": self.dummy_flux_inpaint,
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"INVERSE": self.dummy_inverse,
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"COMPOSE": self.dummy_compose,
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"RESIZE": self.dummy_resize,
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"BBOX": self.dummy_bbox,
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"SOS": self.dummy_sos,
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"FLUX-CBG": self.dummy_flux_cbg,
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"ADD-PRED": self.dummy_add_pred,
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"FLUX-STYLE": self.dummy_flux_style,
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"FLUX-RCM": self.dummy_flux_rcm,
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"FLUX-ENV": self.dummy_flux_env,
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"FLUX-POSE": self.dummy_flux_pose,
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"FLUX-BRIGHT": self.dummy_flux_bright
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}
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```
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Complete your function (dummy_flux_sr) in legodemo.py.
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```python
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def dummy_flux_bright(self, inputs: Dict[str, DataObject]) -> Dict[str, DataObject]:
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image_ori = inputs['image'].copy()
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ratio = inputs['ratio']
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input_value = max(0.0, min(1.0, ratio))
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ratio = 2 * input_value
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image_pil = Image.fromarray(image_ori[:,:,::-1])
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enhancer = ImageEnhance.Brightness(image_pil)
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image_new = enhancer.enhance(ratio)
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image_new = np.array(image_new)[:,:,::-1]
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return {
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"image": image_new
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}
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```
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3οΈβ£ Restart Gradio WebUI
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<p align="center"><img src="https://github.com/xiaomi-research/lego-edit/raw/main/resources/bright.png" width="95%"></p>
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## π More Usages
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Some editing models are trained at a resolution of 768 via the ICEdit method, prioritizing higher output quality over the standard 512 resolution. We provide the corresponding trained [Single-Task-LoRA](https://huggingface.co/xiaomi-research/lego-edit/tree/main/loras). Based on our testing, these models deliver superior performance within their specific functional domains.
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<p align="center"><img src="https://github.com/xiaomi-research/lego-edit/raw/main/resources/lora_effect.png" width="95%"></p>
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You can refer to the usage instructions at [ICEdit](https://github.com/River-Zhang/ICEdit) to use these LoRAs independently.
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## π Disclaimer
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We open-source this project for academic research. The vast majority of images
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used in this project are either generated or licensed. If you have any concerns,
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please contact us, and we will promptly remove any inappropriate content.
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Our code is released under the Apache 2.0 License, while our models are under
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the CC BY-NC 4.0 License. Any models related to <a href="https://huggingface.co/black-forest-labs/FLUX.1-dev" target="_blank">FLUX.1-dev</a>
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base model must adhere to the original licensing terms.
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<br><br>This research aims to advance the field of generative AI. Users are free to
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create images using this tool, provided they comply with local laws and exercise
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responsible usage. The developers are not liable for any misuse of the tool by users.
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## βοΈ Citation
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If this repo is helpful, please help to β it.
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If you find this project useful for your research, please consider citing our paper:
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```bibtex
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@article{jia2025legoedit,
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title = {Lego-Edit: A General Image Editing Framework with Model-Level Bricks and MLLM Builder},
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author = {Qifei Jia and Yu Liu and Yajie Chai and Xintong Yao and Qiming Lu and Yasen Zhang and Runyu Shi and Ying Huang and Guoquan Zhang},
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| 228 |
+
journal = {arXiv preprint arXiv:2509.12883},
|
| 229 |
+
year = {2025},
|
| 230 |
+
url = {https://arxiv.org/abs/2509.12883}
|
| 231 |
+
}
|
| 232 |
+
```
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| 233 |
+
|
| 234 |
+
## π Acknowledgments
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| 235 |
+
|
| 236 |
+
- Built on the [MiMo-VL](https://github.com/XiaomiMiMo/MiMo-VL), [ComfyUI](https://github.com/comfyanonymous/ComfyUI), [FLUX](https://github.com/black-forest-labs/flux), [ICEdit](https://github.com/River-Zhang/ICEdit), [EVF-SAM](https://github.com/hustvl/EVF-SAM) and [LaMa](https://github.com/advimman/lama)
|