Update model card with metadata and paper links

README.md

@@ -1,7 +1,20 @@
+---
+license: other
+library_name: transformers
+pipeline_tag: image-text-to-text
+tags:
+- moe
+- multimodal
+- yuan
+---
+
 <div align="center">
 <h1>
   Yuan3.0 Ultra Multimodal Foundation Large Language Model
 </h1>
+
+[Paper](https://huggingface.co/papers/2601.14327) | [GitHub](https://github.com/Yuan-lab-LLM/Yuan3.0-Ultra)
+
 </div>
 
 <hr>
@@ -207,4 +220,4 @@ Spider 1.0 and BIRD are two major benchmarks in the Text-to-SQL domain. Yuan3.0
 ## 6. License
 Use of Yuan 3.0 code and models must comply with the [Yuan 3.0 Model License Agreement](https://github.com/Yuan-lab-LLM/Yuan3.0?tab=License-1-ov-file). Yuan 3.0 models support commercial use and do not require an application for authorization. Please familiarize yourself with and adhere to the agreement. Do not use the open-source models, code, or any derivatives produced from this open-source project for any purposes that may cause harm to the nation or society, or for any services that have not undergone safety assessment and registration.
 
-Although measures have been taken during training to ensure data compliance and accuracy to the best of our ability, given the enormous scale of model parameters and the influence of probabilistic randomness, we cannot guarantee the accuracy of generated outputs, and models are susceptible to being misled by input instructions. This project assumes no responsibility for data security risks, public opinion risks, or any risks and liabilities arising from the model being misled, misused, disseminated, or improperly exploited due to the use of open-source models and code. You shall bear full and sole responsibility for all risks and consequences arising from your use, copying, distribution, and modification of this open-source project.
+Although measures have been taken during training to ensure data compliance and accuracy to the best of our ability, given the enormous scale of model parameters and the influence of probabilistic randomness, we cannot guarantee the accuracy of generated outputs, and models are susceptible to being misled by input instructions. This project assumes no responsibility for data security risks, public opinion risks, or any risks and liabilities arising from the model being misled, misused, disseminated, or improperly exploited due to the use of open-source models and code. You shall bear full and sole responsibility for all risks and consequences arising from your use, copying, distribution, and modification of this open-source project.