Add `library_name` tag and paper link to model card

README.md

@@ -1,22 +1,23 @@
 ---
-license: apache-2.0
+base_model:
+- microsoft/Phi-3-mini-128k-instruct
+- GoodBaiBai88/M3D-CLIP
+- google/siglip-large-patch16-256
 datasets:
 - GoodBaiBai88/M3D-Cap
 - GoodBaiBai88/M3D-VQA
 language:
 - en
-base_model:
-- microsoft/Phi-3-mini-128k-instruct
-- GoodBaiBai88/M3D-CLIP
-- google/siglip-large-patch16-256
+license: apache-2.0
 pipeline_tag: image-text-to-text
+library_name: transformers
 ---
 
 # Med-2E3-M3D
 
 ## Introduction
 
-A 3D medical LVLM, Med-2E3, trained on **3D** CT volumes and English medical texts ([M3D-Cap](https://huggingface.co/datasets/GoodBaiBai88/M3D-Cap) & [M3D-VQA](https://huggingface.co/datasets/GoodBaiBai88/M3D-VQA)), enabling tasks such as **report generation** and medical **VQA**.
+A 3D medical LVLM, Med-2E3, trained on **3D** CT volumes and English medical texts ([M3D-Cap](https://huggingface.co/datasets/GoodBaiBai88/M3D-Cap) & [M3D-VQA](https://huggingface.co/datasets/GoodBaiBai88/M3D-VQA)), enabling tasks such as **report generation** and medical **VQA**. This model is presented in the paper [Med-2E3: A 2D-Enhanced 3D Medical Multimodal Large Language Model](https://huggingface.co/papers/2411.12783).
 
 | | Config |
 | :--- | :---: |
@@ -40,4 +41,4 @@ Please refer to [Med-2E3](https://github.com/MSIIP/Med-2E3).
   journal={arXiv preprint arXiv:2411.12783},
   year={2024}
 }
-```
+```