Update README.md

README.md

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 **LatexMind-2B-Codec** is designed for tasks that require **image-based text recognition**, **math equation extraction**, and **multi-modal understanding**. It is particularly useful in the following scenarios:  
 
-🔹 **Optical Character Recognition (OCR)** – Extracting printed and handwritten text from images, documents, and scanned pages.  
-🔹 **Math Expression Recognition** – Converting mathematical notations into structured **LaTeX format** for further computation and documentation.  
-🔹 **Image-to-Text Conversion** – Generating accurate descriptions for text-rich and math-heavy images.  
-🔹 **Document and Academic Processing** – Assisting researchers, students, and professionals in digitizing handwritten notes and extracting structured content from books, PDFs, and whiteboards.  
-🔹 **Automated Educational Support** – Enabling AI-powered tutors, content summarization, and interactive learning for subjects involving complex equations.  
-🔹 **Multi-Language OCR** – Recognizing text inside images across multiple languages, including English, Chinese, Japanese, Korean, Arabic, and various European languages.  
-🔹 **Video-Based Question Answering** – Understanding long-duration videos for content summarization, question answering, and structured data extraction.  
+ **Optical Character Recognition (OCR)** – Extracting printed and handwritten text from images, documents, and scanned pages.  
+ **Math Expression Recognition** – Converting mathematical notations into structured **LaTeX format** for further computation and documentation.  
+ **Image-to-Text Conversion** – Generating accurate descriptions for text-rich and math-heavy images.  
+ **Document and Academic Processing** – Assisting researchers, students, and professionals in digitizing handwritten notes and extracting structured content from books, PDFs, and whiteboards.  
+ **Automated Educational Support** – Enabling AI-powered tutors, content summarization, and interactive learning for subjects involving complex equations.  
+ **Multi-Language OCR** – Recognizing text inside images across multiple languages, including English, Chinese, Japanese, Korean, Arabic, and various European languages.  
+ **Video-Based Question Answering** – Understanding long-duration videos for content summarization, question answering, and structured data extraction.  
 
 # Limitations 
 
 Despite its capabilities, **LatexMind-2B-Codec** has some inherent limitations:  
 
-⚠ **Handwritten Text Accuracy** – While it can recognize handwritten equations, performance may degrade with highly unstructured or messy handwriting.  
-⚠ **Complex LaTeX Formatting** – The model may struggle with deeply nested or ambiguous LaTeX expressions, requiring manual corrections for precise formatting.  
-⚠ **Low-Resolution Images** – Extracting accurate text from blurry or low-resolution images can lead to misinterpretations or OCR errors.  
-⚠ **Contextual Understanding in Multi-Step Equations** – While it recognizes math expressions, solving multi-step problems autonomously may be limited.  
-⚠ **Limited Support for Rare Mathematical Notations** – Some specialized or domain-specific symbols may not be recognized with high accuracy.  
-⚠ **Processing Speed for Large Documents** – Performance may slow down when handling extremely large documents or dense mathematical content in real-time applications.  
-⚠ **Language-Specific OCR Variability** – While it supports multiple languages, OCR accuracy may vary depending on the script complexity and font style.
+ **Handwritten Text Accuracy** – While it can recognize handwritten equations, performance may degrade with highly unstructured or messy handwriting.  
+ **Complex LaTeX Formatting** – The model may struggle with deeply nested or ambiguous LaTeX expressions, requiring manual corrections for precise formatting.  
+ **Low-Resolution Images** – Extracting accurate text from blurry or low-resolution images can lead to misinterpretations or OCR errors.  
+ **Contextual Understanding in Multi-Step Equations** – While it recognizes math expressions, solving multi-step problems autonomously may be limited.  
+ **Limited Support for Rare Mathematical Notations** – Some specialized or domain-specific symbols may not be recognized with high accuracy.  
+ **Processing Speed for Large Documents** – Performance may slow down when handling extremely large documents or dense mathematical content in real-time applications.  
+ **Language-Specific OCR Variability** – While it supports multiple languages, OCR accuracy may vary depending on the script complexity and font style.