Update README.md

README.md

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 ## Model Overview
 Index-1.9B-32K is a language model with only 1.9 billion parameters, yet it supports a context length of 32K (meaning this extremely small model can read documents of over 35,000 words in one go). The model has undergone Continue Pre-Training and Supervised Fine-Tuning (SFT) specifically for texts longer than 32K tokens, based on carefully curated long-text training data and self-built long-text instruction sets. The model is now open-source on both Hugging Face and ModelScope.
 
-**Despite its small size (about 2% of models like GPT-4), Index-1.9B-32K demonstrates excellent long-text processing capabilities**. Below are comparison results with GPT-4 and GPT-3.5-turbo-16k:
-<div style="text-align: center;">
-    <img src="z-attach-pic-pk-all.png" alt="" width="800">
-    <p><strong>Comparison of Index-1.9B-32K with GPT-4 and other models in long-text capability</strong></p>
-</div>
+Despite its small size (about 2% of models like GPT-4), Index-1.9B-32K demonstrates excellent long-text processing capabilities. 
+As shown in the figure below, our 1.9B-sized model's score even surpasses that of the 7B-sized model. Below is a comparison with models like GPT-4 and Qwen2:
+
+<p align="center"> <img src="z-attach-pic-pk-all.png" alt="" width="800"> 
+</p> <p align="center"><strong>Comparison of Index-1.9B-32K with GPT-4, Qwen2, and other models in Long Context capability</strong>
+</p>
 
 In a 32K-length needle-in-a-haystack test, Index-1.9B-32K achieved excellent results, as shown in the figure below. The only exception was a small yellow spot (91.08 points) in the region of (32K length, 10% depth), with all other areas performing excellently in mostly green zones.
 <div style="text-align: center;">