Improve model card: add pipeline tag, paper/code links, and sample usage

README.md

@@ -1,24 +1,25 @@
 ---
-license: apache-2.0
-tags:
-  - video-generation
-  - game-rendering
-  - game-editing
-  - diffusion
-  - g-buffer
-  - relighting
-  - text-to-video
-  - wan2.1
-pipeline_tag: text-to-video
 base_model: Wan-AI/Wan2.1-T2V-1.3B
 datasets:
-  - custom
+- custom
 library_name: diffusers
+license: apache-2.0
+pipeline_tag: image-to-video
+tags:
+- video-generation
+- game-rendering
+- game-editing
+- diffusion
+- g-buffer
+- relighting
+- wan2.1
 ---
 
 # Game Editing
 
-**Game Editing** is a fine-tuned video diffusion model for controllable game video synthesis. It enables users to manipulate lighting and environmental effects in game footage via text prompts, conditioned on G-buffer inputs.
+**Game Editing** is a fine-tuned video diffusion model for controllable game video synthesis, presented in the paper [Generative World Renderer](https://huggingface.co/papers/2604.02329). It enables users to manipulate lighting and environmental effects in game footage via text prompts, conditioned on G-buffer inputs.
+
+[**Project Page**](https://alaya-studio.github.io/renderer) | [**GitHub Repository**](https://github.com/ShandaAI/AlayaRenderer) | [**arXiv**](https://arxiv.org/abs/2604.02329)
 
 ## Model Details
 
@@ -31,6 +32,24 @@ library_name: diffusers
 | **Clip Length** | 81 frames |
 | **Format** | SafeTensors |
 
+## Sample Usage
+
+To run inference, please follow the installation instructions in the [official repository](https://github.com/ShandaAI/AlayaRenderer). Below is an example command for running the game editing model:
+
+```bash
+cd game_editing
+
+CUDA_VISIBLE_DEVICES=0 python \
+    examples/wanvideo/model_inference/inference_gbuffer_caption.py \
+    --checkpoint models/train/Wan2.1-T2V-1.3B_gbuffer/model.safetensors \
+    --gpu 0 \
+    --style snowy_winter \
+    --prompt "the scene is set in a frozen, snow-covered environment under cold, pale winter light with falling snowflakes, creating a silent and ethereal winter wonderland atmosphere." \
+    --gbuffer_dir test_dataset \
+    --save_dir outputs/ \
+    --num_frames 81 --height 480 --width 832
+```
+
 ## Inputs
 
 The model takes the following inputs:
@@ -76,4 +95,13 @@ In the absence of directly comparable methods, we establish a baseline by adapti
 
 ## Citation
 
-If you find this model useful, please consider citing our work.
+If you find this model useful, please consider citing the following work:
+
+```bibtex
+@article{huang2026generativeworldrenderer,
+    title={Generative World Renderer},
+    author={Zheng-Hui Huang and Zhixiang Wang and Jiaming Tan and Ruihan Yu and Yidan Zhang and Bo Zheng and Yu-Lun Liu and Yung-Yu Chuang and Kaipeng Zhang},
+    journal={arXiv preprint arXiv:2604.02329},
+    year={2026}
+}
+```