update readme

README.md

@@ -16,9 +16,9 @@ datasets:
 
 ## Introduction
 
-The Imp project aims to provide a family of  a strong multimodal `small` language models (MSLMs). Our `Imp-v1.5-2B-Qwen1.5` is a strong MSLM with only **2B** parameters, which is build upon a small yet powerful SLM [Qwen1.5-1.8B-Chat ](https://huggingface.co/Qwen/Qwen1.5-1.8B-Chat)(1.8B) and a powerful visual encoder [SigLIP ](https://huggingface.co/google/siglip-so400m-patch14-384)(0.4B), and trained on the [LLaVA-v1.5](https://github.com/haotian-liu/LLaVA) training set.  
+The Imp project aims to provide a family of  a strong multimodal `small` language models (MSLMs). Our `Imp-v1.5-2B-Qwen1.5` is a strong MSLM with only **2B** parameters, which is build upon a small yet powerful SLM [Qwen1.5-1.8B-Chat ](https://huggingface.co/Qwen/Qwen1.5-1.8B-Chat)(1.8B) and a powerful visual encoder [SigLIP ](https://huggingface.co/google/siglip-so400m-patch14-384)(0.4B), and trained on on 1M mixed dataset.   
 
-As shown in the Table below, `Imp-v1.5-2B-Qwen1.5` significantly outperforms the counterparts of similar model sizes, and even achieves slightly better performance than the strong LLaVA-7B model on various multimodal benchmarks. 
+As shown in the Table below, `Imp-v1.5-2B-Qwen1.5` significantly outperforms the counterparts of similar model sizes. 
 
 We release our model weights and provide an example below to run our model . Detailed technical report and corresponding training/evaluation code will be released soon on our [GitHub repo](https://github.com/MILVLG/imp). We will persistently improve our model and release the next versions to further improve model performance :) 
 
@@ -85,10 +85,10 @@ This project is maintained by the [MILVLG](https://github.com/MILVLG)@Hangzhou D
 If you use our model or refer our work in your studies, please cite:
 
 ```bibtex
-@misc{imp2024,
-  author = {Shao, Zhenwei and Ouyang, Xuecheng and Yu, Zhou and Yu, Jun},
-  title = {Imp: An Emprical Study of Multimodal Small Language Models},
-  year = {2024},
-  url = {https://huggingface.co/MILVLG/Imp-v1.5-2B-Qwen1.5}
+@article{imp2024,
+  title={Imp: Highly Capable Large Multimodal Models for Mobile Devices},
+  author={Shao, Zhenwei and Yu, Zhou and Yu, Jun and Ouyang, Xuecheng and Lihao, Zheng and Zhenbiao, Gai and Mingyang, Wang and Jiajun, Ding},
+  journal={arXiv preprint arXiv:2405.12107},
+  year={2024}
 }
 ```

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "MILVLG/imp-qwen-v1-2b",
+  "_name_or_path": "MILVLG/Imp-v1.5-2B-Qwen1.5",
   "architectures": [
     "ImpQwen2ForCausalLM"
   ],