Update README.md

README.md

@@ -13,7 +13,7 @@ base_model:
 CRE：A recruitment domain embedding Model. Used for encoding resume or job description texts, serving as the foundation for retrieval, RAG, and Agent. CRE：一个招聘领域的嵌入模型。用于对简历或岗位描述文本进行编码，作为检索、RAG（检索增强生成）和智能体（Agent）的基础。
 2025/3/28 Released the CRE0.5.0 model and technical report. By means of CNN, a local feature-aware inductive bias is introduced to make local features more prominent in text encoding for human resource scenarios. Specifically, this is an auxiliary fine-tuning method. It improves the encoding quality of the base model by adding some model parameters for joint training during fine-tuning, and is essentially a projection layer. 借助CNN，以引入一种局部特征感知的归纳偏好，使在人力资源场景的文本编码中，局部特征更为突出。具体而言，这是一种在辅助微调的方法，通过在微调训练中增加一些模型参数共同训练，从而提高基座模型的编码质量，本质上是一种投影层设计。
 
-![CRE-0.5 introduction](photos/cre_0_5_introduction.png)
+![CRE-0.5 introduction](photos/cre_0_5_introduction.jpg)
 
 ### Using Sentence-Transformers
 ```python