Update model card with metadata and usage instructions

Hi! I'm Niels from the Hugging Face community team. I've updated the model card for TeleStyle to improve its discoverability and usability.

Key changes:
1. Added `library_name: diffusers` to the metadata based on the project's dependencies.
2. Added the `arxiv` ID for better paper integration.
3. Included sample usage (CLI commands) for both image and video stylization from your GitHub repository.
4. Refined the metadata tags.

This should make it easier for users to understand and run your model!

README.md

@@ -1,16 +1,20 @@
 ---
-license: apache-2.0
-language:
-- en
 base_model:
 - Wan-AI/Wan2.1-T2V-1.3B
 - Qwen/Qwen-Image-Edit-2509
-pipeline_tag: any-to-any
+language:
+- en
+license: apache-2.0
+pipeline_tag: other
+library_name: diffusers
+arxiv: 2601.20175
 tags:
 - video
 - image
 - stylization
+- style-transfer
 ---
+
 <div align="center">
 
 <h1><b>TeleStyle: Content-Preserving Style Transfer in Images and Videos</b></h1>
@@ -36,19 +40,41 @@ Shiwen Zhang, Xiaoyan Yang, Bojia Zi, Haibin Huang, Chi Zhang, Xuelong Li
   </a>
 </p>
 
+TeleStyle is a lightweight yet effective model for both image and video stylization. Built upon Qwen-Image-Edit, it leverages a Curriculum Continual Learning framework to achieve high-fidelity content preservation and style customization across diverse, in-the-wild style categories.
 
-## 🔔News
+## 🔔 News
 
 - [2026-01-28]: Released [Code](https://github.com/Tele-AI/TeleStyle), [Model](https://huggingface.co/Tele-AI/TeleStyle), [Paper](http://arxiv.org/abs/2601.20175).
 
 ## How to use
 
-- Please refer to [**🔗 GitHub**](https://github.com/Tele-AI/TeleStyle) for usage.
+### 1. Installation
+
+```bash
+pip install -r requirements.txt
+```
+
+### 2. Inference
+
+We provide inference scripts for running TeleStyle on demo inputs for each task:
+
+#### Image Stylization
+To generate a stylized image using a reference style image and a content image:
+```bash
+python telestyleimage_inference.py --image_path assets/example/0.png --style_path videos/1.png --output_path results/image.png
+```
+
+#### Video Stylization
+To generate a stylized video using a stylized first frame and a content video:
+```bash
+python telestylevideo_inference.py --video_path assets/example/1.mp4 --style_path assets/example/1-0.png --output_path results/video.mp4
+```
 
+For more details, please refer to the [**🔗 GitHub**](https://github.com/Tele-AI/TeleStyle) repository.
 
 ## 🌟 Citation
 
-If you find UniVideo useful for your research and applications, please cite using this BibTeX:
+If you find TeleStyle useful for your research and applications, please cite using this BibTeX:
 
 ```bibtex
 @article{teleai2026telestyle,