Update pipeline tag to video-text-to-text

README.md

@@ -1,22 +1,22 @@
 ---
-license: apache-2.0
-pipeline_tag: image-text-to-text
-library_name: transformers
 base_model:
-  - OpenGVLab/InternVL2.5-1B
-base_model_relation: merge
+- OpenGVLab/InternVL2.5-1B
 language:
-  - multilingual
+- multilingual
+library_name: transformers
+license: apache-2.0
+pipeline_tag: video-text-to-text
 tags:
-  - Sa2VA
-  - custom_code
+- Sa2VA
+- custom_code
+base_model_relation: merge
 ---
 
 # Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos
 
-[\[📂 GitHub\]](https://github.com/magic-research/Sa2VA)
-[\[📜 Sa2VA paper\]](https://arxiv.org/abs/2501.04001)
-[\[🚀 Quick Start\]](#quick-start) 
+[\\[📂 GitHub\\]](https://github.com/magic-research/Sa2VA)
+[\\[📜 Sa2VA paper\\]](https://arxiv.org/abs/2501.04001)
+[\\[🚀 Quick Start\\]](#quick-start) 
 
 
 
@@ -152,8 +152,8 @@ If you find this project useful in your research, please consider citing:
 ```BibTeX
 @article{sa2va,
   title={Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos},
-  author={Yuan, Haobo and Li, Xiangtai and Zhang, Tao and Huang, Zilong Huang and Xu, Shilin and Ji, Shunping and Tong, Yunhai and Qi, Lu and Feng, Jiashi and Yang, Ming-Hsuan},
+  author={Yuan, Haobo and Li, Xiangtai and Zhang, Tao and Huang, Zilong and Xu, Shilin and Ji, Shunping and Tong, Yunhai and Qi, Lu and Feng, Jiashi and Yang, Ming-Hsuan},
   journal={arXiv preprint},
   year={2025}
 }
-```
+```