Update README.md

README.md

@@ -27,7 +27,9 @@ print('runing time:', genertaion_time)
 
 |                          model_name                          | vqav2 | gqa   | sqa | textvqa  | MM-VET | POPE | MME  | MMMU |
 | :----------------------------------------------------------: | ----- | ------- | ----- | ----- | ------- | ----- | ------ | ------ |
+| [LLaVA-1.5-7B](https://huggingface.co/bczhou/TinyLLaVA-3.1B) |  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   | - |
+| [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 |
 
 P.S. TinyLLaVA Factory is an open-source modular codebase for small-scale LMMs with a focus on simplicity of code implementations, extensibility of new features, and reproducibility of training results. This code repository provides standard training&evaluating pipelines, flexible data preprocessing&model configurations, and easily extensible architectures. Users can customize their own LMMs with minimal coding effort and less codding mistake.