--- license: apache-2.0 pipeline_tag: any-to-any tags: - UniCharacter - customized-multimodal-role-play - multimodal-role-play - character-customization - text-to-image - image-generation --- # UniCharacter UniCharacter is a collection of character-specific checkpoints for **Customized Multimodal Role-Play (CMRP)**, introduced in the paper [Towards Customized Multimodal Role-Play](https://arxiv.org/abs/2605.08129). [**Project Page**](https://tangc03.github.io/UniCharacter.github.io/) | [**GitHub**](https://github.com/Tangc03/UniCharacter) | [**Paper**](https://arxiv.org/abs/2605.08129) The model is designed to customize a character's persona, dialogue style, and visual identity so that the character can respond consistently across text and image generation settings. Using a unified multimodal model, UniCharacter employs a two-stage training framework containing Unified Supervised Finetuning (Unified-SFT) and character-specific group relative policy optimization (Character-GRPO). ## Repository Contents This repository contains separate checkpoint folders for multiple characters. Each character directory includes sharded `safetensors` weights and a `model.safetensors.index.json` file. Available character folders include: - `Adrien_Brody`, `Bo`, `Butin`, `Chandler`, `Coco`, `Furina`, `Gao_Qiqiang`, `Hermione`, `Ichihime`, `Joey`, `Leonardo`, `Mam`, `Miki_Nikaidou`, `Mydieu`, `Pikachu`, `Rin_Tohsaka`, `Saber`, `Will_In_Vietnam`, `Wukong`, `YuiYagi` ## Quick Usage Example To use these checkpoints, please follow the installation instructions in the [official repository](https://github.com/Tangc03/UniCharacter). Below is an example of the unified inference interface: ```python from inference import create_unicharacter_inference from pathlib import Path # Initialize the unified inference (modify paths according to your environment) inference = create_unicharacter_inference( model_path="models/BAGEL-7B-MoT", checkpoint_path=" ", vit_checkpoint_path=" ", max_mem_per_gpu="40GiB", seed=42, ) out_dir = Path("test_images/outputs") out_dir.mkdir(parents=True, exist_ok=True) # 1) Text-to-image generation (Role T2I) res = inference.generate_image("Ichihime chasing a butterfly") res["image"].save(out_dir / "t2i_ichihime.png") # 2) Visual understanding / VQA res = inference.visual_understanding( "data/personalized_data/train/Mahjong Soul-Ichihime/1.png", "What's the color of Ichihime's hair?", ) print("VQA:", res["text"]) # 3) Knowledge QA res = inference.knowledge_qa("When do you born?") print("Knowledge QA:", res["text"]) # 4) Multimodal role-play res = inference.role_play( character_name="Ichihime", description="", opening="", user_text="Hi, Ichihime. How are you?", ) print("Role-play:", res["response"]) ``` ## Download Download the full repository: ```bash huggingface-cli download Tangc03/UniCharacter --local-dir UniCharacter ``` Download a single character checkpoint folder: ```bash huggingface-cli download Tangc03/UniCharacter --include "Hermione/*" --local-dir UniCharacter ``` ## Citation If you use UniCharacter, please cite: ```bibtex @article{tang2026towards, title={Towards Customized Multimodal Role-Play}, author={Tang, Chao and Wu, Jianzong and Shi, Qingyu and Tian, Ye and Zhang, Aixi and Jiang, Hao and Zhang, Jiangning and Tong, Yunhai}, journal={arXiv preprint arXiv:2605.08129}, year={2026} } ```
