Update README.md

README.md

@@ -4,6 +4,11 @@ pipeline_tag: visual-question-answering
 ---
 # 😈 Imp
 
+> A very small man can cast a very large shadow.
+> 
+>           ——*George R.R. Martin, A Clash of Kings*
+
+
 \[Technical report (coming soon)\]  [[Demo](https://xmbot,net/imp/)\]  [[Github](https://github.com/MILVLG/imp)\]
 
 ## Introduction
@@ -53,7 +58,7 @@ print(tokenizer.decode(output_ids[input_ids.shape[1]:], skip_special_tokens=True
 ## Model evaluation
 We conduct evaluation on 9 commonly-used benchmarks, including 5 academic VQA benchmarks and 4 popular MLLM benchmarks, to compare our Imp model with LLaVA (7B) and existing MSLMs of similar model sizes.
 
-| Models | Size | VQAv2 | GQA |VizWiz  | SQA (IMG) | TextVQA | POPE |  MME | MMB  |MM-Vet|
+| Models | Size | VQAv2 | GQA |VizWiz  | SQA(IMG) | TextVQA | POPE |  MME(P) | MMB  |MM-Vet|
 |:--------:|:-----:|:----:|:----:|:-------------:|:--------:|:-----:|:----:|:-------:|:-------:|:-------:|
 | [LLaVA-v1.5-lora](https://huggingface.co/liuhaotian/llava-v1.5-7b) | 7B |79.10 | **63.00** |47.80 |  68.40 |58.20| 86.40 | **1476.9** | 66.10  |30.2|
 | [TinyGPT-V](https://huggingface.co/Tyrannosaurus/TinyGPT-V) | 3B | - | 33.60  | 24.80  |    -   |    -  | -| - | -  |-|