Enhance model card with metadata, introduction, usage, and citation
Browse filesThis PR significantly enhances the model card for InstanceAssemble by adding crucial metadata and expanding the descriptive content.
Key improvements include:
- Adding the `pipeline_tag: text-to-image` to improve discoverability and enable the automated Hugging Face inference widget.
- Specifying `library_name: diffusers` to provide a ready-to-use code snippet for users, based on compatibility evidence with SD3/Flux models.
- Incorporating the model's introduction, a visual teaser, and practical usage examples with code snippets directly from the GitHub README, making it easier for users to understand and get started with the model.
- Adding the paper citation from the GitHub repository.
- Retaining the existing license and GitHub repository link.
Please review these updates.
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---
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license: apache-2.0
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---
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This repository contains the model used in [InstanceAssemble: Layout-Aware Image Generation via Instance Assembling Attention](https://arxiv.org/abs/2509.16691).
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---
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license: apache-2.0
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pipeline_tag: text-to-image
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library_name: diffusers
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---
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# InstanceAssemble
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> Official implementation of "InstanceAssemble: Layout-Aware Image Generation via Instance Assembling Attention" (NeurIPS 2025).
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<p align="center">
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<img src="https://github.com/FireRedTeam/InstanceAssemble/raw/main/fig/teaser.jpg" alt="Teaser of InstanceAssemble" width="800">
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</p>
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This repository contains the model used in [InstanceAssemble: Layout-Aware Image Generation via Instance Assembling Attention](https://arxiv.org/abs/2509.16691).
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## Introduction
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InstanceAssemble is a lightweight framework for Layout-to-Image generation that enables precise spatial control. We also introduce DenseLayout and Layout Grounding Score (LGS) for rigorous evaluation, where InstanceAssemble achieves state-of-the-art performance on both sparse and dense layouts.
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For the official code and more details, please refer to the GitHub repository: [https://github.com/FireRedTeam/InstanceAssemble](https://github.com/FireRedTeam/InstanceAssemble).
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## Usage
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### Inference
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```bash
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# sd3 based
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python inference.py --model_type sd3 --input_json ./demo/bigchair.json
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# flux based
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python inference.py --model_type fluxdev --input_json ./demo/bigchair.json
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python inference.py --model_type fluxschnell --input_json ./demo/bigchair.json
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```
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### Streamlit demo
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```bash
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streamlit run demo.py
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```
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## Citation
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```
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@article{xiang2025instanceassemble,
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title={InstanceAssemble: Layout-Aware Image Generation via Instance Assembling Attention},
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author={Qiang Xiang and Shuang Sun and Binglei Li and Dejia Song and Huaxia Li and Nemo Chen and Xu Tang and Yao Hu and Junping Zhang},
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journal={arXiv preprint arXiv:2509.16691},
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year={2025},
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}
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```
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