Update README.md

README.md

@@ -4,10 +4,10 @@ language:
 - en
 pipeline_tag: visual-question-answering
 ---
-# :smiling_imp: IMP
+# 😈 IMP
 
 
-The :smiling_imp: IMP project aims to provide a family of  a strong multimodal `small` language models (MSLMs). Our `IMP-v0-3B` model is a strong MSLM with only **3B** parameters, which is build upon a small yet powerful SLM [Phi-2 ](https://huggingface.co/microsoft/phi-2)(2.7B) 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-v0-3B` model is a strong MSLM with only **3B** parameters, which is build upon a small yet powerful SLM [Phi-2 ](https://huggingface.co/microsoft/phi-2)(2.7B) 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.  
 
 As shown in the Table below, `IMP-v0-3B` significantly outperforms the counterparts of similar model sizes, and even achieves slightly better performance than the strong LLaVA-7B model on various multimodal benchmarks.