Update README.md

README.md

@@ -3,8 +3,11 @@ license: apache-2.0
 pipeline_tag: image-text-to-text
 ---
 
-### TinyLLaVA
-We introduce TinyLLaVA-Phi-2-SigLIP-3.1B, a small-scale large multimodal model(LMM), which is trained by the TinyLLaVA Factory codebase. For the LLM and vision tower, we choose [Phi-2](microsoft/phi-2) and [siglip-so400m-patch14-384](https://huggingface.co/google/siglip-so400m-patch14-384), respectively. The dataset used for training this model is the [ShareGPT4V](https://github.com/InternLM/InternLM-XComposer/blob/main/projects/ShareGPT4V/docs/Data.md) dataset.
+### <span style="font-size:2em;">TinyLLaVA</span>
+[![hf_space](https://img.shields.io/badge/🤗-%20Open%20In%20HF-blue.svg)](https://huggingface.co/tinyllava) [![arXiv](https://img.shields.io/badge/Arxiv-2402.14289-b31b1b.svg?logo=arXiv)](https://arxiv.org/abs/2402.14289) [![Github](https://img.shields.io/badge/Github-Github-orange.svg)](https://github.com/TinyLLaVA/TinyLLaVA_Factory) [![Doc](https://img.shields.io/badge/Doc-Document-logo=read%20the%20docs&logoColor=white&label=Doc)](https://tinyllava-factory.readthedocs.io/en/latest/) [![Demo](https://img.shields.io/badge/Demo-Demo-red.svg)](http://8843843nmph5.vicp.fun/#/)
+TinyLLaVA has released a family of small-scale Large Multimodel Models(LMMs), ranging from 1.4B to 3.1B. Our best model, TinyLLaVA-Phi-2-SigLIP-3.1B, achieves better overall performance against existing 7B models such as LLaVA-1.5 and Qwen-VL.
+
+Here, we introduce TinyLLaVA-Phi-2-SigLIP-3.1B, which is trained by the TinyLLaVA Factory codebase. For LLM and vision tower, we choose [Phi-2](microsoft/phi-2) and [siglip-so400m-patch14-384](https://huggingface.co/google/siglip-so400m-patch14-384), respectively. The dataset used for training this model is the [ShareGPT4V](https://github.com/InternLM/InternLM-XComposer/blob/main/projects/ShareGPT4V/docs/Data.md) dataset.
 
 ### Usage
 Execute the following test code:
@@ -28,7 +31,7 @@ print('runing time:', genertaion_time)
 |                          model_name                          | vqav2 | gqa   | sqa | textvqa  | MM-VET | POPE | MME  | MMMU |
 | :----------------------------------------------------------: | ----- | ------- | ----- | ----- | ------- | ----- | ------ | ------ |
 | [LLaVA-1.5-7B](https://huggingface.co/llava-hf/llava-1.5-7b-hf) |  78.5  | 62.0    |  66.8  |  58.2 | 30.5  | 85.9 | 1510.7   | - |
-| [bczhou/TinyLLaVA-3.1B](https://huggingface.co/bczhou/TinyLLaVA-3.1B) | 79.9  | 62.0    | 69.1  | 59.1 | 32.0  | 86.4  | 1464.9   | - |
+| [bczhou/TinyLLaVA-3.1B](https://huggingface.co/bczhou/TinyLLaVA-3.1B) (legacy model) | 79.9  | 62.0    | 69.1  | 59.1 | 32.0  | 86.4  | 1464.9   | - |
 | [tinyllava/TinyLLaVA-Gemma-SigLIP-2.4B](https://huggingface.co/tinyllava/TinyLLaVA-Gemma-SigLIP-2.4B) | 78.4 | 61.6   | 64.4 | 53.6 | 26.9 | 86.4  | 1339.0 | 31.7 |
 | [tinyllava/TinyLLaVA-Phi-2-SigLIP-3.1B](https://huggingface.co/tinyllava/TinyLLaVA-Phi-2-SigLIP-3.1B) | 80.1 | 62.1   | 73.0 | 60.3 | 37.5 | 87.2  | 1466.4 | 38.4 |