Update README.md

README.md

@@ -17,3 +17,17 @@ tags:
 # **ChemQwen-vL [ Qwen for Chemistry Vision ]**
 
 *ChemQwen-vL* is a vision-language model fine-tuned based on the Qwen2VL-2B Instruct model. It has been trained using the International Chemical Identifier (InChI) format and is optimized for chemical component identification. The model excels at generating the InChI and providing descriptions of chemical compounds based on their images. Its architecture, derived from Qwen2-VL, can handle images of arbitrary resolutions by mapping them into a dynamic number of visual tokens. This offers a more human-like visual processing experience. The model operates in a multi-modal framework, combining image-text-text capabilities.
+
+Here’s how the **Key Enhancements** section for **ChemQwen-vL** could look with the requested style:  
+
+---
+
+# **Key Enhancements**
+
+* **State-of-the-art understanding of chemical images**: ChemQwen-vL delivers top-tier performance in analyzing chemical images of varying resolutions and ratios, ensuring precise InChI generation and structural descriptions.  
+
+* **Advanced processing of chemical sequences**: Capable of handling complex molecular structures and long sequences, ChemQwen-vL is ideal for tasks requiring detailed chemical reasoning and compound analysis.  
+
+* **Integration with automated laboratory systems**: With its powerful reasoning and decision-making capabilities, ChemQwen-vL can integrate with laboratory robotics, enabling autonomous chemical analysis and reporting based on image and text inputs.  
+
+* **Multilingual Chemical Text Support**: To support global scientific communities, ChemQwen-vL understands chemical texts in multiple languages, including English, Chinese, German, French, Japanese, Korean, Arabic, and more, for enhanced accessibility and collaboration.