Update README.md

README.md

@@ -15,7 +15,7 @@ Execute the following test code:
 ```python
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
-hf_path = 'Zhang199/TinyLLaVA-Qwen2-SigLIP-0.5B'
+hf_path = 'Zhang199/TinyLLaVA-Qwen2-0.5B-SigLIP'
 model = AutoModelForCausalLM.from_pretrained(hf_path, trust_remote_code=True)
 model.cuda()
 config = model.config
@@ -34,7 +34,7 @@ print('runing time:', genertaion_time)
 | [bczhou/TinyLLaVA-3.1B](https://huggingface.co/bczhou/TinyLLaVA-3.1B) (our 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 |
-| [Zhang199/TinyLLaVA-Qwen2-SigLIP-0.5B](https://huggingface.co/Zhang199/TinyLLaVA-Qwen2-0.5B-siglip-so400m-patch14-384-base) | 72.33 | 55.84 | 60.14 | 45.17 | 19.5 | 86.59  | 1153 | 29.7 |
+| [Zhang199/TinyLLaVA-Qwen2-0.5B-SigLIP](https://huggingface.co/Zhang199/TinyLLaVA-Qwen2-0.5B-siglip-so400m-patch14-384-base) | 72.33 | 55.84 | 60.14 | 45.17 | 19.5 | 86.59  | 1153 | 29.7 |
 
 P.S. [TinyLLaVA Factory](https://github.com/TinyLLaVA/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 coding mistake.